Matrix based computation of floating-point roundoff noise. - Barry D. Van Veen; Richard G. Baraniuk (IEEE Trans. Acoust. Speech Signal Process., 1989)

A radially-Gaussian, signal-dependent time-frequency representation. - Richard G. Baraniuk; Douglas L. Jones (ICASSP, 1991)

New dimensions in wavelet analysis. - Richard G. Baraniuk; Douglas L. Jones (ICASSP, 1992)

Shear Madness: Signal-Dependent and Metaplectic Time-Frequency Representations - Richard G. Baraniuk (1992)

Warped wavelet bases: unitary equivalence and signal processing. - Richard G. Baraniuk; Douglas L. Jones (ICASSP (3), 1993)

Signal-dependent time-frequency analysis using a radially Gaussian kernel. - Richard G. Baraniuk; Douglas L. Jones (Signal Process., 1993)

A signal-dependent time-frequency representation: optimal kernel design. - Richard G. Baraniuk; Douglas L. Jones (IEEE Trans. Signal Process., 1993)

Shear madness: new orthonormal bases and frames using chirp functions. - Richard G. Baraniuk; Douglas L. Jones (IEEE Trans. Signal Process., 1993)

Time-frequency complexity and information. - Patrick Flandrin; Richard G. Baraniuk; Olivier J. J. Michel (ICASSP (3), 1994)

Wavelet Soft-Thresholding of Time-Frequency Representations. - Richard G. Baraniuk (ICIP (1), 1994)

A signal-dependent time-frequency representation: fast algorithm for optimal kernel design. - Richard G. Baraniuk; Douglas L. Jones (IEEE Trans. Signal Process., 1994)

A simple scheme for adapting time-frequency representations. - Douglas L. Jones; Richard G. Baraniuk (IEEE Trans. Signal Process., 1994)

Marginals vs. covariance in joint distribution theory. - Richard G. Baraniuk (ICASSP, 1995)

Warping time-frequency and time-scale representations to match signals. - Richard G. Baraniuk (Visual Information Processing, 1995)

On joint distributions for arbitrary variables. - Richard G. Baraniuk; Leon Cohen (IEEE Signal Process. Lett., 1995)

Unitary equivalence: a new twist on signal processing. - Richard G. Baraniuk; Douglas L. Jones (IEEE Trans. Signal Process., 1995)

An adaptive optimal-kernel time-frequency representation. - Douglas L. Jones; Richard G. Baraniuk (IEEE Trans. Signal Process., 1995)

Pseudo affine Wigner distributions. - Paulo Gonçalves; Richard G. Baraniuk (ICASSP, 1996)

Optimal phase kernels for time-frequency analysis. - L. Fridtjof Wisur-Olsen; Richard G. Baraniuk (ICASSP, 1996)

A limitation of the kernel method for joint distributions of arbitrary variables. - Richard G. Baraniuk (IEEE Signal Process. Lett., 1996)

Covariant time-frequency representations through unitary equivalence. - Richard G. Baraniuk (IEEE Signal Process. Lett., 1996)

A pseudo-Bertrand distribution for time-scale analysis. - Paulo Gonçalves; Richard G. Baraniuk (IEEE Signal Process. Lett., 1996)

Myoelectric teleoperation of a complex robotic hand. - Kristin A. Farry; Ian D. Walker; Richard G. Baraniuk (IEEE Trans. Robotics Autom., 1996)

Wigner-based formulation of the chirplet transform. - Richard G. Baraniuk; Douglas L. Jones (IEEE Trans. Signal Process., 1996)

Signal estimation using wavelet-Markov models. - Matthew S. Crouse; Richard G. Baraniuk; Robert D. Nowak (ICASSP, 1997)

Improved type-based detection of analog signals. - Don H. Johnson; Paulo Gonçalves; Richard G. Baraniuk (ICASSP, 1997)

Adaptive Wavelet Transforms for Image Coding Using Lifting. - Roger Claypool; Geoffrey M. Davis; Wim Sweldens; Richard G. Baraniuk (Data Compression Conference, 1998)

Adaptive wavelet transforms via lifting. - Roger L. Claypoole Jr.; Richard G. Baraniuk; Robert D. Nowak (ICASSP, 1998)

Simplified wavelet-domain hidden Markov models using contexts. - Matthew S. Crouse; Richard G. Baraniuk (ICASSP, 1998)

Joint Distributions of Arbitrary Variables Made Easy. - Richard G. Baraniuk (Multidimens. Syst. Signal Process., 1998)

Adaptive weighted highpass filters using multiscale analysis. - Robert D. Nowak; Richard G. Baraniuk (IEEE Trans. Image Process., 1998)

Beyond time-frequency analysis: energy densities in one and many dimensions. - Richard G. Baraniuk (IEEE Trans. Signal Process., 1998)

Wavelet-based statistical signal processing using hidden Markov models. - Matthew S. Crouse; Robert D. Nowak; Richard G. Baraniuk (IEEE Trans. Signal Process., 1998)

Pseudo affine Wigner distributions: definition and kernel formulation. - Paulo Gonçalves; Richard G. Baraniuk (IEEE Trans. Signal Process., 1998)

Interpolation and denoising of nonuniformly sampled data using wavelet-domain processing. - Hyeokho Choi; Richard G. Baraniuk (ICASSP, 1999)

Wavelet-based deconvolution for ill-conditioned systems. - Ramesh Neelamani; Hyeokho Choi; Richard G. Baraniuk (ICASSP, 1999)

Multiple Basis Wavelet Denoising Using BESOV Projections. - Hyeokho Choi; Richard G. Baraniuk (ICIP (1), 1999)

Wavelet-Domain Regularized Deconvolution for ILL-Conditioned Systems. - Ramesh Neelamani; Hyeokho Choi; Richard G. Baraniuk (ICIP (1), 1999)

Bayesian Wavelet-Domain Image Modeling Using Hidden Markov Trees. - Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (ICIP (1), 1999)

Simulation of nonGaussian Long-Range-Dependent Traffic Using Wavelets. - Vinay J. Ribeiro; Rudolf H. Riedi; Matthew S. Crouse; Richard G. Baraniuk (SIGMETRICS, 1999)

Wavelet-domain filtering for photon imaging systems. - Robert D. Nowak; Richard G. Baraniuk (IEEE Trans. Image Process., 1999)

A Multifractal Wavelet Model with Application to Network Traffic. - Rudolf H. Riedi; Matthew S. Crouse; Vinay J. Ribeiro; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 1999)

Wavelet-based transformations for nonlinear signal processing. - Robert D. Nowak; Richard G. Baraniuk (IEEE Trans. Signal Process., 1999)

Hybrid linear/bilinear time-scale analysis. - Martin Pasquier; Paulo Gonçalves; Richard G. Baraniuk (IEEE Trans. Signal Process., 1999)

Multiscale document segmentation using wavelet-domain hidden Markov models. - Hyeokho Choi; Richard G. Baraniuk (Document Recognition and Retrieval, 2000)

Hidden Markov tree modeling of complex wavelet transforms. - Hyeokho Choi; Justin K. Romberg; Richard G. Baraniuk; Nick G. Kingsbury (ICASSP, 2000)

Wavelet folding and decorrelation across the scale. - Jun Feng Tian; Richard G. Baraniuk; Raymond O. Wells Jr.; Damian M. Tan; Hong Ren Wu (ICASSP, 2000)

Imaging with THZ Pulses. - Timothy Dorney; Jon Johnson; Daniel M. Mittleman; Richard G. Baraniuk (ICIP, 2000)

Model-Based Inverse Halftoning with Wavelet-Vaguelette Deconvolution. - Ramesh Neelamani; Robert D. Nowak; Richard G. Baraniuk (ICIP, 2000)

Multiscale Classification Using Complex Wavelets and Hidden Markov Tree Models. - Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk; Nick G. Kingsbury (ICIP, 2000)

Multiscale Queuing Analysis of Long-Range-Dependent Network Traffic. - Vinay J. Ribeiro; Rudolf H. Riedi; Matthew S. Crouse; Richard G. Baraniuk (INFOCOM, 2000)

Spectroscopic Imaging Using Terahertz Time-Domain Signals. - Timothy Dorney; Richard G. Baraniuk; Daniel M. Mittleman; Robert D. Nowak (SSIAI, 2000)

Bayesian Tree-Structured Image Modeling. - Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (SSIAI, 2000)

Optimal transmit spectra for communication in the presence of crosstalk and imperfect echo cancellation. - Nadeem Ahmed; Richard G. Baraniuk; Donald P. Shaver (GLOBECOM, 2001)

Wavelets and multifractals for network traffic modeling and inference. - Vinay J. Ribeiro; Rudolf H. Riedi; Richard G. Baraniuk (ICASSP, 2001)

Multiscale image processing using normal triangulated meshes. - M. Jansen; Hyeokho Choi; Sridhar Lavu; Richard G. Baraniuk (ICIP (2), 2001)

Compression color space estimation of JPEG images using lattice basis reduction. - Ramesh Neelamani; Ricardo L. de Queiroz; Richard G. Baraniuk (ICIP (1), 2001)

Multiscale edge grammars for complex wavelet transforms. - Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (ICIP (1), 2001)

Connection-level analysis and modeling of network traffic. - Shriram Sarvotham; Rudolf H. Riedi; Richard G. Baraniuk (Internet Measurement Workshop, 2001)

Lattice algorithms for compression color space estimation in JPEG images. - Ramesh Neelamani; Ricardo L. de Queiroz; Richard G. Baraniuk (IWCIA, 2001)

Multiscale image segmentation using wavelet-domain hidden Markov models. - Hyeokho Choi; Richard G. Baraniuk (IEEE Trans. Image Process., 2001)

Bayesian tree-structured image modeling using wavelet-domain hidden Markov models. - Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (IEEE Trans. Image Process., 2001)

Measuring time-Frequency information content using the Rényi entropies. - Richard G. Baraniuk; Patrick Flandrin; Augustus J. E. M. Janssen; Olivier J. J. Michel (IEEE Trans. Inf. Theory, 2001)

Hybrid linear/quadratic time-frequency attributes. - Richard G. Baraniuk; Mark Coates; Philippe Steeghs (IEEE Trans. Signal Process., 2001)

Image Compression using an Efficient Edge Cartoon + Texture Model. - Michael B. Wakin; Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (DCC, 2002)

Asymptotic performance of transmit diversity via OFDM for multipath channels. - Nadeem Ahmed; Richard G. Baraniuk (GLOBECOM, 2002)

Connexions: DSP education for a networked world. - Richard G. Baraniuk; C. Sidney Burrus; B. M. Hendricks; G. L. Henry; Alfred O. Hero III; Don H. Johnson; Douglas L. Jones; Julius Kusuma; Robert D. Nowak; J. E. Odegard; Lee C. Potter; Kannan Ramchandran; et al. (ICASSP, 2002)

Additive and multiplicative mixture trees for network traffic modeling. - Shriram Sarvotham; Xin Wang; Rudolf H. Riedi; Richard G. Baraniuk (ICASSP, 2002)

Multiscale wedgelet image analysis: fast decompositions and modeling. - Justin K. Romberg; Michael B. Wakin; Richard G. Baraniuk (ICIP (3), 2002)

Rate-distortion optimized image compression using wedgelets. - Justin K. Romberg; Michael B. Wakin; Hyeokho Choi; Richard G. Baraniuk (ICIP (3), 2002)

Near Best Tree Approximation. - Richard G. Baraniuk; Ronald A. DeVore; George Kyriazis; X. M. Yu (Adv. Comput. Math., 2002)

Multiscale nature of network traffic. - Patrice Abry; Richard G. Baraniuk; Patrick Flandrin; Rudolf H. Riedi; Darryl Veitch (IEEE Signal Process. Mag., 2002)

Estimation-Quantization Geometry Coding Using Normal Meshes. - Sridhar Lavu; Hyeokho Choi; Richard G. Baraniuk (DCC, 2003)

Open-content signal processing laboratories in connexions. - Swaroop Appadwedula; Richard G. Baraniuk; Matthew Berry; Mark D. Butala; Hyeokho Choi; Mark A. Haun; Douglas L. Jones; Michael L. Kramer; Dima Moussa; Lee C. Potter; Daniel Grobe Sachs; Brian Wade; et al. (ICASSP (3), 2003)

Orthogonal Hilbert transform filter banks and wavelets. - Rutger L. van Spaendonck; Thierry Blu; Richard G. Baraniuk; Martin Vetterli (ICASSP (6), 2003)

JPEG compression history estimation for color images. - Ramesh Neelamani; Ricardo L. de Queiroz; Zhigang Fan 001; Richard G. Baraniuk (ICIP (3), 2003)

Approximation and compression of piecewise smooth images using a wavelet/wedgelet geometric model. - Justin K. Romberg; Michael B. Wakin; Richard G. Baraniuk (ICIP (1), 2003)

Distributed image compression for sensor networks using correspondence analysis and super-resolution. - Raymond S. Wagner; Robert D. Nowak; Richard G. Baraniuk (ICIP (1), 2003)

Geometry Compression of Normal Meshes Using Rate-Distortion Algorithms. - Sridhar Lavu; Hyeokho Choi; Richard G. Baraniuk (Symposium on Geometry Processing, 2003)

Multiscale geometric image processing. - Justin K. Romberg; Michael B. Wakin; Richard G. Baraniuk (VCIP, 2003)

Nonlinear wavelet transforms for image coding via lifting. - Roger L. Claypoole Jr.; Geoffrey M. Davis; Wim Sweldens; Richard G. Baraniuk (IEEE Trans. Image Process., 2003)

Delay-limited throughput maximization for fading channels using rate and power control. - Nadeem Ahmed; Mohammad Ali Khojestapour; Richard G. Baraniuk (GLOBECOM, 2004)

Directional hypercomplex wavelets for multidimensional signal analysis and processing. - Wai Lam Chan; Hyeokho Choi; Richard G. Baraniuk (ICASSP (3), 2004)

Non-redundant, linear-phase, semi-orthogonal, directional complex wavelets [image/video processing applications]. - Felix C. A. Fernandes; Michael B. Wakin; Richard G. Baraniuk (ICASSP (2), 2004)

Contraction, smoothness, and low-pass filtering. - Mohammad Ali Khojastepour; Behnaam Aazhang; Richard G. Baraniuk (ICASSP (2), 2004)

Quaternion wavelets for image analysis and processing. - Wai Lam Chan; Hyeokho Choi; Richard G. Baraniuk (ICIP, 2004)

Robust distributed estimation in sensor networks using the embedded polygons algorithm. - Véronique Delouille; Ramesh Neelamani; Richard G. Baraniuk (IPSN, 2004)

Surflets: a sparse representation for multidimensional functions containing smooth discontinuities. - Venkat Chandrasekaran; Michael B. Wakin; Dror Baron; Richard G. Baraniuk (ISIT, 2004)

Spatio-temporal available bandwidth estimation with STAB. - Vinay J. Ribeiro; Rudolf H. Riedi; Richard G. Baraniuk (SIGMETRICS, 2004)

Locating Available Bandwidth Bottlenecks. - Vinay J. Ribeiro; Rudolf H. Riedi; Richard G. Baraniuk (IEEE Internet Comput., 2004)

Multiple wavelet basis image denoising using Besov ball projections. - Hyeokho Choi; Richard G. Baraniuk (IEEE Signal Process. Lett., 2004)

Sharing knowledge and building communities in signal processing. - Richard G. Baraniuk; C. Sidney Burrus; Don H. Johnson; Douglas L. Jones (IEEE Signal Process. Mag., 2004)

Joint signaling techniques and spectral optimization for symmetric bit-rate communication over self-NEXT-dominated channels. - Rohit V. Gaikwad; Richard G. Baraniuk (IEEE Trans. Commun., 2004)

ForWaRD: Fourier-wavelet regularized deconvolution for ill-conditioned systems. - Ramesh Neelamani; Hyeokho Choi; Richard G. Baraniuk (IEEE Trans. Signal Process., 2004)

Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks. - Santashil PalChaudhuri; Rajnish Kumar; Richard G. Baraniuk; David B. Johnson 001 (DCOSS, 2005)

Multiscale manifold representation and modeling. - Hyeokho Choi; Richard G. Baraniuk (ICASSP (4), 2005)

A multiscale data representation for distributed sensor networks. - Raymond S. Wagner; Shriram Sarvotham; Richard G. Baraniuk (ICASSP (4), 2005)

High-resolution navigation on non-differentiable image manifolds. - Michael B. Wakin; David L. Donoho; Hyeokho Choi; Richard G. Baraniuk (ICASSP (5), 2005)

TCP-Africa: an adaptive and fair rapid increase rule for scalable TCP. - R. King; Richard G. Baraniuk; Rudolf H. Riedi (INFOCOM, 2005)

Recovery of Jointly Sparse Signals from Few Random Projections. - Michael B. Wakin; Marco F. Duarte; Shriram Sarvotham; Dror Baron; Richard G. Baraniuk (NIPS, 2005)

Network and user driven alpha-beta on-off source model for network traffic. - Shriram Sarvotham; Rudolf H. Riedi; Richard G. Baraniuk (Comput. Networks, 2005)

The dual-tree complex wavelet transform. - Ivan W. Selesnick; Richard G. Baraniuk; Nick G. Kingsbury (IEEE Signal Process. Mag., 2005)

Distributed Wavelet De-Noising for Sensor Networks. - Raymond S. Wagner; Véronique Delouille; Richard G. Baraniuk (CDC, 2006)

A new compressive imaging camera architecture using optical-domain compression. - Dharmpal Takhar; Jason N. Laska; Michael B. Wakin; Marco F. Duarte; Dror Baron; Shriram Sarvotham; Kevin F. Kelly; Richard G. Baraniuk (Computational Imaging, 2006)

Coding vs. Packet Retransmission over Noisy Channels. - Dror Baron; Shriram Sarvotham; Richard G. Baraniuk (CISS, 2006)

Controlling False Alarms With Support Vector Machines. - Mark A. Davenport; Richard G. Baraniuk; Clayton D. Scott (ICASSP (5), 2006)

Sparse Signal Detection from Incoherent Projections. - Marco F. Duarte; Mark A. Davenport; Michael B. Wakin; Richard G. Baraniuk (ICASSP (3), 2006)

Random Filters for Compressive Sampling and Reconstruction. - Joel A. Tropp; Michael B. Wakin; Marco F. Duarte; Dror Baron; Richard G. Baraniuk (ICASSP (3), 2006)

Random Projections of Signal Manifolds. - Michael B. Wakin; Richard G. Baraniuk (ICASSP (5), 2006)

Multiscale Image Disparity Estimation using the Quaternion Wavelet Transform. - Wai Lam Chan; Hyeokho Choi; Richard G. Baraniuk (ICIP, 2006)

An Architecture for Compressive Imaging. - Michael B. Wakin; Jason N. Laska; Marco F. Duarte; Dror Baron; Shriram Sarvotham; Dharmpal Takhar; Kevin F. Kelly; Richard G. Baraniuk (ICIP, 2006)

Universal distributed sensing via random projections. - Marco F. Duarte; Michael B. Wakin; Dror Baron; Richard G. Baraniuk (IPSN, 2006)

An architecture for distributed wavelet analysis and processing in sensor networks. - Raymond S. Wagner; Richard G. Baraniuk; Shu Du; David B. Johnson 001; Albert Cohen 002 (IPSN, 2006)

Sudocodes ߝ Fast Measurement and Reconstruction of Sparse Signals. - Shriram Sarvotham; Dror Baron; Richard G. Baraniuk (ISIT, 2006)

JPEG compression history estimation for color images. - Ramesh Neelamani; Ricardo L. de Queiroz; Zhigang Fan 001; Sanjeeb Dash; Richard G. Baraniuk (IEEE Trans. Image Process., 2006)

Wavelet-domain approximation and compression of piecewise smooth images. - Michael B. Wakin; Justin K. Romberg; Hyeokho Choi; Richard G. Baraniuk (IEEE Trans. Image Process., 2006)

Faster sequential universal coding via block partitioning. - Dror Baron; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2006)

Multiscale queueing analysis. - Vinay J. Ribeiro; Rudolf H. Riedi; Richard G. Baraniuk (IEEE/ACM Trans. Netw., 2006)

Robust Distributed Estimation Using the Embedded Subgraphs Algorithm. - Véronique Delouille; Ramesh Neelamani; Richard G. Baraniuk (IEEE Trans. Signal Process., 2006)

The smashed filter for compressive classification and target recognition. - Mark A. Davenport; Marco F. Duarte; Michael B. Wakin; Jason N. Laska; Dharmpal Takhar; Kevin F. Kelly; Richard G. Baraniuk (Computational Imaging, 2007)

Quantization of Sparse Representations. - Petros Boufounos; Richard G. Baraniuk (DCC, 2007)

Multiscale Random Projections for Compressive Classification. - Marco F. Duarte; Mark A. Davenport; Michael B. Wakin; Jason N. Laska; Dharmpal Takhar; Kevin F. Kelly; Richard G. Baraniuk (ICIP (6), 2007)

Locally Competitive Algorithms for Sparse Approximation. - Christopher J. Rozell; Don H. Johnson; Richard G. Baraniuk; Bruno A. Olshausen (ICIP (4), 2007)

Blind Error-Free Detection of Transform-Domainwatermarks. - Mona A. Sheikh; Richard G. Baraniuk (ICIP (5), 2007)

Theory and Implementation of an Analog-to-Information Converter using Random Demodulation. - Jason N. Laska; Sami Kirolos; Marco F. Duarte; Tamer Ragheb; Richard G. Baraniuk; Yehia Massoud (ISCAS, 2007)

Random Projections for Manifold Learning. - Chinmay Hegde; Michael B. Wakin; Richard G. Baraniuk (NIPS, 2007)

On Nearly Orthogonal Lattice Bases and Random Lattices. - Ramesh Neelamani; Sanjeeb Dash; Richard G. Baraniuk (SIAM J. Discret. Math., 2007)

Compressive Sensing [Lecture Notes]. - Richard G. Baraniuk (IEEE Signal Process. Mag., 2007)

IEEE-SPS and Connexions - An Open Access Education Collaboration [Society News]. - Richard G. Baraniuk; C. Sidney Burrus; E. Joel Thierstein (IEEE Signal Process. Mag., 2007)

Texas Two-Step: A Framework for Optimal Multi-Input Single-Output Deconvolution. - Ramesh Neelamani; Max Deffenbaugh; Richard G. Baraniuk (IEEE Trans. Image Process., 2007)

Probe Design for Compressive Sensing DNA Microarrays. - Wei Dai 001; Olgica Milenkovic; Mona A. Sheikh; Richard G. Baraniuk (BIBM, 2008)

Compressive sensing. - Richard G. Baraniuk (CISS, 2008)

1-Bit compressive sensing. - Petros Boufounos; Richard G. Baraniuk (CISS, 2008)

Compressive Sensing for Background Subtraction. - Volkan Cevher; Aswin C. Sankaranarayanan; Marco F. Duarte; Dikpal Reddy; Richard G. Baraniuk; Rama Chellappa (ECCV (2), 2008)

Distributed target localization via spatial sparsity. - Volkan Cevher; Marco F. Duarte; Richard G. Baraniuk (EUSIPCO, 2008)

Reconstructing sparse signals from their zero crossings. - Petros Boufounos; Richard G. Baraniuk (ICASSP, 2008)

Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model. - Marco F. Duarte; Michael B. Wakin; Richard G. Baraniuk (ICASSP, 2008)

On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion. - Stephen Pfetsch; Tamer Ragheb; Jason N. Laska; Hamid Nejati; Anna C. Gilbert; Martin Strauss 001; Richard G. Baraniuk; Yehia Massoud (ISCAS, 2008)

Sparse Signal Recovery Using Markov Random Fields. - Volkan Cevher; Marco F. Duarte; Chinmay Hegde; Richard G. Baraniuk (NIPS, 2008)

Viewpoint: Global warming toward open educational resources. - Richard G. Baraniuk; C. Sidney Burrus (Commun. ACM, 2008)

Sparse Coding via Thresholding and Local Competition in Neural Circuits. - Christopher J. Rozell; Don H. Johnson; Richard G. Baraniuk; Bruno A. Olshausen (Neural Comput., 2008)

Peer Review Anew: Three Principles and a Case Study in Postpublication Quality Assurance. - Christopher M. Kelty; C. Sidney Burrus; Richard G. Baraniuk (Proc. IEEE, 2008)

Compressive Sampling [From the Guest Editors]. - Richard G. Baraniuk; Emmanuel J. Candès; Robert D. Nowak; Martin Vetterli (IEEE Signal Process. Mag., 2008)

Single-pixel imaging via compressive sampling. - Marco F. Duarte; Mark A. Davenport; Dharmpal Takhar; Jason N. Laska; Ting Sun; Kevin F. Kelly; Richard G. Baraniuk (IEEE Signal Process. Mag., 2008)

Coherent Multiscale Image Processing Using Dual-Tree Quaternion Wavelets. - Wai Lam Chan; Hyeokho Choi; Richard G. Baraniuk (IEEE Trans. Image Process., 2008)

Sparse Geodesic Paths. - Mark A. Davenport; Richard G. Baraniuk (AAAI Fall Symposium: Manifold Learning and Its Applications, 2009)

Model-based compressive sensing for signal ensembles. - Marco F. Duarte; Volkan Cevher; Richard G. Baraniuk (Allerton, 2009)

Compressive sensing of streams of pulses. - Chinmay Hegde; Richard G. Baraniuk (Allerton, 2009)

Recovery of compressible signals in unions of subspaces. - Marco F. Duarte; Chinmay Hegde; Volkan Cevher; Richard G. Baraniuk (CISS, 2009)

Near-optimal Bayesian localization via incoherence and sparsity. - Volkan Cevher; Petros Boufounos; Richard G. Baraniuk; Anna C. Gilbert; Martin J. Strauss (IPSN, 2009)

A Theoretical Analysis of Joint Manifolds - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (CoRR, 2009)

Distributed Compressive Sensing - Dror Baron; Marco F. Duarte; Michael B. Wakin; Shriram Sarvotham; Richard G. Baraniuk (CoRR, 2009)

A simple proof that random matrices are democratic - Mark A. Davenport; Jason N. Laska; Petros Boufounos; Richard G. Baraniuk (CoRR, 2009)

Compressive Sensing DNA Microarrays. - Wei Dai 001; Mona A. Sheikh; Olgica Milenkovic; Richard G. Baraniuk (EURASIP J. Bioinform. Syst. Biol., 2009)

Random Projections of Smooth Manifolds. - Richard G. Baraniuk; Michael B. Wakin (Found. Comput. Math., 2009)

Representation and Compression of Multidimensional Piecewise Functions Using Surflets. - Venkat Chandrasekaran; Michael B. Wakin; Dror Baron; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2009)

High Dimensional Data Fusion via Joint Manifold Learning. - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Recovery of frequency-sparse signals from compressive measurements. - Marco F. Duarte; Richard G. Baraniuk (Allerton, 2010)

Compressive Acquisition of Dynamic Scenes. - Aswin C. Sankaranarayanan; Pavan K. Turaga; Richard G. Baraniuk; Rama Chellappa (ECCV (1), 2010)

Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation. - Eva L. Dyer; Marco F. Duarte; Don H. Johnson; Richard G. Baraniuk (LVA/ICA, 2010)

Kronecker product matrices for compressive sensing. - Marco F. Duarte; Richard G. Baraniuk (ICASSP, 2010)

Compressive sensing of a superposition of pulses. - Chinmay Hegde; Richard G. Baraniuk (ICASSP, 2010)

Texas Hold 'Em algorithms for distributed compressive sensing. - Stephen R. Schnelle; Jason N. Laska; Chinmay Hegde; Marco F. Duarte; Mark A. Davenport; Richard G. Baraniuk (ICASSP, 2010)

Introduction to the Issue on Compressive Sensing. - Rick Chartrand; Richard G. Baraniuk; Yonina C. Eldar; Mário A. T. Figueiredo; Jared Tanner (IEEE J. Sel. Top. Signal Process., 2010)

Signal Processing With Compressive Measurements. - Mark A. Davenport; Petros Boufounos; Michael B. Wakin; Richard G. Baraniuk (IEEE J. Sel. Top. Signal Process., 2010)

Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. - Mark A. Davenport; Richard G. Baraniuk; Clayton D. Scott (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Applications of Sparse Representation and Compressive Sensing. - Richard G. Baraniuk; Emmanuel J. Candès; Michael Elad; Yi Ma 001 (Proc. IEEE, 2010)

Low-Dimensional Models for Dimensionality Reduction and Signal Recovery: A Geometric Perspective. - Richard G. Baraniuk; Volkan Cevher; Michael B. Wakin (Proc. IEEE, 2010)

Sparse Signal Recovery and Acquisition with Graphical Models. - Volkan Cevher; Piotr Indyk; Lawrence Carin; Richard G. Baraniuk (IEEE Signal Process. Mag., 2010)

Joint Manifolds for Data Fusion. - Mark A. Davenport; Chinmay Hegde; Marco F. Duarte; Richard G. Baraniuk (IEEE Trans. Image Process., 2010)

Model-based compressive sensing. - Richard G. Baraniuk; Volkan Cevher; Marco F. Duarte; Chinmay Hegde (IEEE Trans. Inf. Theory, 2010)

Beyond Nyquist: efficient sampling of sparse bandlimited signals. - Joel A. Tropp; Jason N. Laska; Marco F. Duarte; Justin K. Romberg; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2010)

Bayesian compressive sensing via belief propagation. - Dror Baron; Shriram Sarvotham; Richard G. Baraniuk (IEEE Trans. Signal Process., 2010)

The polyphase random demodulator for wideband compressive sensing. - Jason N. Laska; John P. Slavinsky; Richard G. Baraniuk (ACSCC, 2011)

Suboptimality of nonlocal means on images with sharp edges. - Arian Maleki; Manjari Narayan; Richard G. Baraniuk (Allerton, 2011)

Go with the flow: Optical flow-based transport operators for image manifolds. - Aswin C. Sankaranarayanan; Chinmay Hegde; Sriram Nagaraj; Richard G. Baraniuk (Allerton, 2011)

Recovery guarantees for restoration and separation of approximately sparse signals. - Christoph Studer; Richard G. Baraniuk (Allerton, 2011)

Robust support recovery using sparse compressive sensing matrices. - Jarvis D. Haupt; Richard G. Baraniuk (CISS, 2011)

The compressive multiplexer for multi-channel compressive sensing. - John P. Slavinsky; Jason N. Laska; Mark A. Davenport; Richard G. Baraniuk (ICASSP, 2011)

Least favorable compressed sensing problems for first-order methods. - Arian Maleki; Richard G. Baraniuk (ISIT, 2011)

SpaRCS: Recovering low-rank and sparse matrices from compressive measurements. - Andrew E. Waters; Aswin C. Sankaranarayanan; Richard G. Baraniuk (NIPS, 2011)

Bounds on the Reconstruction of Sparse Signal Ensembles from Distributed Measurements - Marco F. Duarte; Michael B. Wakin; Dror Baron; Shriram Sarvotham; Richard G. Baraniuk (CoRR, 2011)

Deterministic Bounds for Restricted Isometry of Compressed Sensing Matrices - Shriram Sarvotham; Richard G. Baraniuk (CoRR, 2011)

The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range - Mark A. Davenport; Jason N. Laska; John R. Treichler; Richard G. Baraniuk (CoRR, 2011)

Stable Restoration and Separation of Approximately Sparse Signals - Christoph Studer; Richard G. Baraniuk (CoRR, 2011)

A Theory for Optical flow-based Transport on Image Manifolds - Sriram Nagaraj; Aswin C. Sankaranarayanan; Richard G. Baraniuk (CoRR, 2011)

Anisotropic Nonlocal Means Denoising - Arian Maleki; Manjari Narayan; Richard G. Baraniuk (CoRR, 2011)

Learning Low-Dimensional Signal Models. - Lawrence Carin; Richard G. Baraniuk; Volkan Cevher; David B. Dunson; Michael I. Jordan; Guillermo Sapiro; Michael B. Wakin (IEEE Signal Process. Mag., 2011)

Sampling and Recovery of Pulse Streams. - Chinmay Hegde; Richard G. Baraniuk (IEEE Trans. Signal Process., 2011)

Trust, But Verify: Fast and Accurate Signal Recovery From 1-Bit Compressive Measurements. - Jason N. Laska; Zaiwen Wen; Wotao Yin; Richard G. Baraniuk (IEEE Trans. Signal Process., 2011)

Signal representations with minimum ℓ∞-norm. - Christoph Studer; Wotao Yin; Richard G. Baraniuk (Allerton Conference, 2012)

A compressive phase-locked loop. - Stephen R. Schnelle; John P. Slavinsky; Petros Boufounos; Mark A. Davenport; Richard G. Baraniuk (ICASSP, 2012)

Dictionary learning from sparsely corrupted or compressed signals. - Christoph Studer; Richard G. Baraniuk (ICASSP, 2012)

A bit-constrained sar adc for compressive acquisition of frequency sparse signals. - Andrew E. Waters; Charles K. Sestok; Richard G. Baraniuk (ICASSP, 2012)

CS-MUVI: Video compressive sensing for spatial-multiplexing cameras. - Aswin C. Sankaranarayanan; Christoph Studer; Richard G. Baraniuk (ICCP, 2012)

SPIN: Iterative signal recovery on incoherent manifolds. - Chinmay Hegde; Richard G. Baraniuk (ISIT, 2012)

Minimum complexity pursuit: Stability analysis. - Shirin Jalali; Arian Maleki; Richard G. Baraniuk (ISIT, 2012)

Sequentially designed compressed sensing. - Jarvis D. Haupt; Richard G. Baraniuk; Rui M. Castro; Robert D. Nowak (SSP, 2012)

Near-isometric linear embeddings of manifolds. - Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk (SSP, 2012)

Multi-objective sensor-based replanning for a car-like robot. - Devin K. Grady; Mark Moll; Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk; Lydia E. Kavraki (SSRR, 2012)

Multi-robot target verification with reachability constraints. - Devin K. Grady; Mark Moll; Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk; Lydia E. Kavraki (SSRR, 2012)

VLSI Design of Approximate Message Passing for Signal Restoration and Compressive Sensing. - Patrick Maechler; Christoph Studer; David E. Bellasi; Arian Maleki; Andreas Burg 001; Norbert Felber; Hubert Kaeslin; Richard G. Baraniuk (IEEE J. Emerg. Sel. Topics Circuits Syst., 2012)

Trends in Signal Processing Education [In the Spotlight]. - Richard G. Baraniuk; Wayne T. Padgett (IEEE Signal Process. Mag., 2012)

Kronecker Compressive Sensing. - Marco F. Duarte; Richard G. Baraniuk (IEEE Trans. Image Process., 2012)

Signal Recovery on Incoherent Manifolds. - Chinmay Hegde; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2012)

The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range. - Mark A. Davenport; Jason N. Laska; John R. Treichler; Richard G. Baraniuk (IEEE Trans. Signal Process., 2012)

Regime Change: Bit-Depth Versus Measurement-Rate in Compressive Sensing. - Jason N. Laska; Richard G. Baraniuk (IEEE Trans. Signal Process., 2012)

Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. - Andrew S. Lan; Christoph Studer; Andrew E. Waters; Richard G. Baraniuk (EDM, 2013)

Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. - Andrew S. Lan; Christoph Studer; Andrew E. Waters; Richard G. Baraniuk (EDM, 2013)

Test-size Reduction for Concept Estimation. - Divyanshu Vats; Christoph Studer; Andrew S. Lan; Lawrence Carin; Richard G. Baraniuk (EDM, 2013)

Compressive sensing radar: Simulation and experiments for target detection. - Laura Anitori; Wim Van Rossum; Matern Otten; Arian Maleki; Richard G. Baraniuk (EUSIPCO, 2013)

Bayesian pairwise collaboration detection in educational datasets. - Andrew E. Waters; Christoph Studer; Richard G. Baraniuk (GlobalSIP, 2013)

Adaptive step size selection for optimization via the ski rental problem. - Amirali Aghazadeh; Ali Ayremlou; Daniel D. Calderon; Tom Goldstein; Raajen Patel; Divyanshu Vats; Richard G. Baraniuk (ICASSP, 2013)

Subspace clustering with dense representations. - Eva L. Dyer; Christoph Studer; Richard G. Baraniuk (ICASSP, 2013)

Open online platforms advancing DSP education. - John P. Slavinsky; Kim J. Davenport; Andrew C. Butler; Elizabeth J. Marsh; Richard G. Baraniuk (ICASSP, 2013)

When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements. - Divyanshu Vats; Richard G. Baraniuk (NIPS, 2013)

The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video. - Tom Goldstein; Lina Xu; Kevin F. Kelly; Richard G. Baraniuk (CoRR, 2013)

Asymptotic Analysis of LASSOs Solution Path with Implications for Approximate Message Passing. - Ali Mousavi 003; Arian Maleki; Richard G. Baraniuk (CoRR, 2013)

Parameterless Optimal Approximate Message Passing. - Ali Mousavi 003; Arian Maleki; Richard G. Baraniuk (CoRR, 2013)

Swapping Variables for High-Dimensional Sparse Regression from Correlated Measurements. - Divyanshu Vats; Richard G. Baraniuk (CoRR, 2013)

Maximin Analysis of Message Passing Algorithms for Recovering Block Sparse Signals - Armeen Taeb; Arian Maleki; Christoph Studer; Richard G. Baraniuk (CoRR, 2013)

Greedy feature selection for subspace clustering. - Eva L. Dyer; Aswin C. Sankaranarayanan; Richard G. Baraniuk (J. Mach. Learn. Res., 2013)

Compressive Acquisition of Linear Dynamical Systems. - Aswin C. Sankaranarayanan; Pavan K. Turaga; Rama Chellappa; Richard G. Baraniuk (SIAM J. Imaging Sci., 2013)

Measurement Bounds for Sparse Signal Ensembles via Graphical Models. - Marco F. Duarte; Michael B. Wakin; Dror Baron; Shriram Sarvotham; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2013)

Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors. - Laurent Jacques; Jason N. Laska; Petros T. Boufounos; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2013)

Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP). - Arian Maleki; Laura Anitori; Zai Yang; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2013)

Design and Analysis of Compressed Sensing Radar Detectors. - Laura Anitori; Arian Maleki; Matern Otten; Richard G. Baraniuk; Peter Hoogeboom (IEEE Trans. Signal Process., 2013)

Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression. - Divyanshu Vats; Richard G. Baraniuk (AISTATS, 2014)

Active Learning for Undirected Graphical Model Selection. - Divyanshu Vats; Robert D. Nowak; Richard G. Baraniuk (AISTATS, 2014)

Quantized Matrix Completion for Personalized Learning. - Andrew S. Lan; Christoph Studer; Richard G. Baraniuk (EDM, 2014)

LIE operators for compressive sensing. - Chinmay Hegde; Aswin C. Sankaranarayanan; Richard G. Baraniuk (ICASSP, 2014)

Matrix recovery from quantized and corrupted measurements. - Andrew S. Lan; Christoph Studer; Richard G. Baraniuk (ICASSP, 2014)

Time-varying learning and content analytics via sparse factor analysis. - Andrew S. Lan; Christoph Studer; Richard G. Baraniuk (KDD, 2014)

Toward Compressive Camera Networks. - Kaushik Mitra; Ashok Veeraraghavan; Aswin C. Sankaranarayanan; Richard G. Baraniuk (Computer, 2014)

Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit. - Ali Ayremlou; Thomas A. Goldstein; Ashok Veeraraghavan; Richard G. Baraniuk (CoRR, 2014)

A Field Guide to Forward-Backward Splitting with a FASTA Implementation. - Tom Goldstein; Christoph Studer; Richard G. Baraniuk (CoRR, 2014)

Sparse Bilinear Logistic Regression. - Jianing Shi; Yangyang Xu; Richard G. Baraniuk (CoRR, 2014)

Video Compressive Sensing for Dynamic MRI. - Jianing Shi; Wotao Yin; Aswin C. Sankaranarayanan; Richard G. Baraniuk (CoRR, 2014)

Democratic Representations. - Christoph Studer; Tom Goldstein; Wotao Yin; Richard G. Baraniuk (CoRR, 2014)

Sparse factor analysis for learning and content analytics. - Andrew S. Lan; Andrew E. Waters; Christoph Studer; Richard G. Baraniuk (J. Mach. Learn. Res., 2014)

Fast Alternating Direction Optimization Methods. - Tom Goldstein; Brendan O'Donoghue; Simon Setzer; Richard G. Baraniuk (SIAM J. Imaging Sci., 2014)

Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. - Rebecca M. Willett; Marco F. Duarte; Mark A. Davenport; Richard G. Baraniuk (IEEE Signal Process. Mag., 2014)

Minimum Complexity Pursuit for Universal Compressed Sensing. - Shirin Jalali; Arian Maleki; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2014)

Compressive Sensing. - Aswin C. Sankaranarayanan; Richard G. Baraniuk (Computer Vision, A Reference Guide, 2014)

Iterative reconstruction from limited angle, limited view projections for cryo-electron tomography. - Sally L. Wood; Ernesto Fontenla; Christopher A. Metzler; Wah Chiu; Richard G. Baraniuk (ACSSC, 2015)

An information-theoretic measure of dependency among variables in large datasets. - Ali Mousavi 003; Richard G. Baraniuk (Allerton, 2015)

A deep learning approach to structured signal recovery. - Ali Mousavi 003; Ankit B. Patel; Richard G. Baraniuk (Allerton, 2015)

Dynamic model generation for application of compressed sensing to cryo-electron tomography reconstruction. - Sally L. Wood; Ernesto Fontenla; Christopher A. Metzler; Wah Chiu; Richard G. Baraniuk (SP/SPE, 2015)

FlatCam: Replacing Lenses with Masks and Computation. - M. Salman Asif; Ali Ayremlou; Ashok Veeraraghavan; Richard G. Baraniuk; Aswin C. Sankaranarayanan (ICCV Workshops, 2015)

BM3D-AMP: A new image recovery algorithm based on BM3D denoising. - Christopher A. Metzler; Arian Maleki; Richard G. Baraniuk (ICIP, 2015)

Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. - Andrew S. Lan; Divyanshu Vats; Andrew E. Waters; Richard G. Baraniuk (L@S, 2015)

BayesRank: A Bayesian Approach to Ranked Peer Grading. - Andrew E. Waters; David Tinapple; Richard G. Baraniuk (L@S, 2015)

FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation. - M. Salman Asif; Ali Ayremlou; Aswin C. Sankaranarayanan; Ashok Veeraraghavan; Richard G. Baraniuk (CoRR, 2015)

Self-Expressive Decompositions for Matrix Approximation and Clustering. - Eva L. Dyer; Tom Goldstein; Raajen Patel; Konrad P. Körding; Richard G. Baraniuk (CoRR, 2015)

FASTA: A Generalized Implementation of Forward-Backward Splitting. - Tom Goldstein; Christoph Studer; Richard G. Baraniuk (CoRR, 2015)

RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets. - Azalia Mirhoseini; Eva L. Dyer; Ebrahim M. Songhori; Richard G. Baraniuk; Farinaz Koushanfar (CoRR, 2015)

Consistent Parameter Estimation for LASSO and Approximate Message Passing. - Ali Mousavi 003; Arian Maleki; Richard G. Baraniuk (CoRR, 2015)

oASIS: Adaptive Column Sampling for Kernel Matrix Approximation. - Raajen Patel; Thomas A. Goldstein; Eva L. Dyer; Azalia Mirhoseini; Richard G. Baraniuk (CoRR, 2015)

A Probabilistic Theory of Deep Learning. - Ankit B. Patel; Minh Tan Nguyen; Richard G. Baraniuk (CoRR, 2015)

Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models. - Aswin C. Sankaranarayanan; Lina Xu; Christoph Studer; Yun Li; Kevin F. Kelly; Richard G. Baraniuk (SIAM J. Imaging Sci., 2015)

The STOne Transform: Multi-Resolution Image Enhancement and Compressive Video. - Tom Goldstein; Lina Xu; Kevin F. Kelly; Richard G. Baraniuk (IEEE Trans. Image Process., 2015)

NuMax: A Convex Approach for Learning Near-Isometric Linear Embeddings. - Chinmay Hegde; Aswin C. Sankaranarayanan; Wotao Yin; Richard G. Baraniuk (IEEE Trans. Signal Process., 2015)

Optimal ranking of test items using the Rasch model. - Divyanshu Vats; Andrew S. Lan; Christoph Studer; Richard G. Baraniuk (Allerton, 2016)

A Contextual Bandits Framework for Personalized Learning Action Selection. - Andrew S. Lan; Richard G. Baraniuk (EDM, 2016)

BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising. - Christopher A. Metzler; Arian Maleki; Richard G. Baraniuk (ICME Workshops, 2016)

Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. - Andrew S. Lan; Tom Goldstein; Richard G. Baraniuk; Christoph Studer (ICML, 2016)

A Probabilistic Framework for Deep Learning. - Ankit B. Patel; Minh Tan Nguyen; Richard G. Baraniuk (NIPS, 2016)

Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition. - Raajen Patel; Tom Goldstein; Eva L. Dyer; Azalia Mirhoseini; Richard G. Baraniuk (SDM, 2016)

Near-Isometric Binary Hashing for Large-scale Datasets. - Amirali Aghazadeh; Andrew S. Lan; Anshumali Shrivastava; Richard G. Baraniuk (CoRR, 2016)

One-Bit Compressive Sensing of Dictionary-Sparse Signals. - Richard G. Baraniuk; Simon Foucart; Deanna Needell; Yaniv Plan; Mary Wootters (CoRR, 2016)

Semi-Supervised Learning with the Deep Rendering Mixture Model. - Minh Tan Nguyen; Wanjia Liu; Ethan Perez; Richard G. Baraniuk; Ankit B. Patel (CoRR, 2016)

Signal Processing for Computational Photography and Displays [From the Guest Editors]. - Amit K. Agrawal; Richard G. Baraniuk; Pablo Favaro; Ashok Veeraraghavan (IEEE Signal Process. Mag., 2016)

MOOC Adventures in Signal Processing: Bringing DSP to the era of massive open online courses. - Thomas A. Baran; Richard G. Baraniuk; Alan V. Oppenheim; Paolo Prandoni; Martin Vetterli (IEEE Signal Process. Mag., 2016)

Lensless Imaging: A computational renaissance. - Vivek Boominathan; Jesse K. Adams; M. Salman Asif; Benjamin W. Avants; Jacob T. Robinson; Richard G. Baraniuk; Aswin C. Sankaranarayanan; Ashok Veeraraghavan (IEEE Signal Process. Mag., 2016)

From Denoising to Compressed Sensing. - Christopher A. Metzler; Arian Maleki; Richard G. Baraniuk (IEEE Trans. Inf. Theory, 2016)

DeepCodec: Adaptive sensing and recovery via deep convolutional neural networks. - Ali Mousavi 003; Gautam Dasarathy; Richard G. Baraniuk (Allerton, 2017)

Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks. - Joshua J. Michalenko; Andrew S. Lan; Richard G. Baraniuk (EDM, 2017)

Data-Mining Textual Responses to Uncover Misconception Patterns. - Joshua J. Michalenko; Andrew S. Lan; Andrew E. Waters; Phillip Grimaldi; Richard G. Baraniuk (EDM, 2017)

A Latent Factor Model For Instructor Content Preference Analysis. - Jack Z. Wang; Andrew S. Lan; Phillip Grimaldi; Richard G. Baraniuk (EDM, 2017)

Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning. - Andrew E. Waters; Phillip Grimaldi; Andrew S. Lan; Richard G. Baraniuk (EDM, 2017)

Contextual multi-armed bandit algorithms for personalized learning action selection. - Indu Manickam; Andrew S. Lan; Richard G. Baraniuk (ICASSP, 2017)

Learning to invert: Signal recovery via Deep Convolutional Networks. - Ali Mousavi 003; Richard G. Baraniuk (ICASSP, 2017)

Flat focus: depth of field analysis for the FlatCam lensless imaging system. - Jasper Tan; Vivek Boominathan; Ashok Veeraraghavan; Richard G. Baraniuk (ICASSP, 2017)

Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset. - Christopher A. Metzler; Manoj Kumar Sharma; Sudarshan Nagesh; Richard G. Baraniuk; Oliver Cossairt; Ashok Veeraraghavan (ICCP, 2017)

RHash: Robust Hashing via L_infinity-norm Distortion. - Amirali Aghazadeh; Andrew S. Lan; Anshumali Shrivastava; Richard G. Baraniuk (IJCAI, 2017)

Sketched covariance testing: A compression-statistics tradeoff. - Gautam Dasarathy; Parikshit Shah; Richard G. Baraniuk (ISIT, 2017)

D.TRUMP: Data-mining Textual Responses to Uncover Misconception Patterns. - Joshua J. Michalenko; Andrew S. Lan; Richard G. Baraniuk (L@S, 2017)

Learned D-AMP: Principled Neural Network based Compressive Image Recovery. - Christopher A. Metzler; Ali Mousavi 003; Richard G. Baraniuk (NIPS, 2017)

Learned D-AMP: A Principled CNN-based Compressive Image Recovery Algorithm. - Christopher A. Metzler; Ali Mousavi 003; Richard G. Baraniuk (CoRR, 2017)

Data-Mining Textual Responses to Uncover Misconception Patterns. - Joshua J. Michalenko; Andrew S. Lan; Richard G. Baraniuk (CoRR, 2017)

Adaptive Partitioning Spline Neural Networks: Template Matching, Memorization, Inhibitor Connections, Inversion, Semi-Sup, Topology Search. - Randall Balestriero; Richard G. Baraniuk (CoRR, 2017)

Semi-Supervised Learning via New Deep Network Inversion. - Randall Balestriero; Vincent Roger; Hervé Glotin; Richard G. Baraniuk (CoRR, 2017)

Overcomplete Frame Thresholding for Acoustic Scene Analysis. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Ankit B. Patel (CoRR, 2017)

BLAh: Boolean Logic Analysis for Graded Student Response Data. - Andrew S. Lan; Andrew E. Waters; Christoph Studer; Richard G. Baraniuk (IEEE J. Sel. Top. Signal Process., 2017)

Introduction to the Issue on Signal Processing and Machine Learning. - Mihaela van der Schaar; Richard G. Baraniuk; Mung Chiang; Jonathan Huang; Shengdong Zhao 001 (IEEE J. Sel. Top. Signal Process., 2017)

Compressive Video Sensing: Algorithms, architectures, and applications. - Richard G. Baraniuk; Thomas A. Goldstein; Aswin C. Sankaranarayanan; Christoph Studer; Ashok Veeraraghavan; Michael B. Wakin (IEEE Signal Process. Mag., 2017)

FlatCam: Thin, Lensless Cameras Using Coded Aperture and Computation. - M. Salman Asif; Ali Ayremlou; Aswin C. Sankaranarayanan; Ashok Veeraraghavan; Richard G. Baraniuk (IEEE Trans. Computational Imaging, 2017)

Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals. - Richard G. Baraniuk; Simon Foucart; Deanna Needell; Yaniv Plan; Mary Wootters (IEEE Trans. Inf. Theory, 2017)

Conveying language through haptics: a multi-sensory approach. - Nathan Dunkelberger; Jennifer L. Sullivan; Joshua Bradley; Nickolas P. Walling; Indu Manickam; Gautam Dasarathy; Ali Israr; Frances W. Y. Lau; Keith Klumb; Brian Knott; Freddy Abnousi; Richard G. Baraniuk; et al. (UbiComp, 2018)

An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing. - Christopher A. Metzler; Philip Schniter; Richard G. Baraniuk (LVA/ICA, 2018)

MISSION: Ultra Large-Scale Feature Selection using Count-Sketches. - Amirali Aghazadeh; Ryan Spring; Daniel LeJeune; Gautam Dasarathy; Anshumali Shrivastava; Richard G. Baraniuk (ICML, 2018)

A Spline Theory of Deep Networks. - Randall Balestriero; Richard G. Baraniuk (ICML, 2018)

Spline Filters For End-to-End Deep Learning. - Randall Balestriero; Romain Cosentino; Hervé Glotin; Richard G. Baraniuk (ICML, 2018)

prDeep: Robust Phase Retrieval with a Flexible Deep Network. - Christopher A. Metzler; Philip Schniter; Ashok Veeraraghavan; Richard G. Baraniuk (ICML, 2018)

QG-net: a data-driven question generation model for educational content. - Zichao Wang 001; Andrew S. Lan; Weili Nie; Andrew E. Waters; Phillip J. Grimaldi; Richard G. Baraniuk (L@S, 2018)

Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion. - Randall Balestriero; Hervé Glotin; Richard G. Baraniuk (CoRR, 2018)

prDeep: Robust Phase Retrieval with Flexible Deep Neural Networks. - Christopher A. Metzler; Philip Schniter; Ashok Veeraraghavan; Richard G. Baraniuk (CoRR, 2018)

A Spline Theory of Deep Networks (Extended Version). - Randall Balestriero; Richard G. Baraniuk (CoRR, 2018)

Unsupervised Learning with Stein's Unbiased Risk Estimator. - Christopher A. Metzler; Ali Mousavi 003; Reinhard Heckel; Richard G. Baraniuk (CoRR, 2018)

Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning. - Nhat Ho; Tan M. Nguyen; Ankit B. Patel; Anima Anandkumar; Michael I. Jordan; Richard G. Baraniuk (CoRR, 2018)

Insense: Incoherent sensor selection for sparse signals. - Amirali Aghazadeh; Mohammad Golbabaee; Andrew S. Lan; Richard G. Baraniuk (Signal Process., 2018)

RankMap: A Framework for Distributed Learning From Dense Data Sets. - Azalia Mirhoseini; Eva L. Dyer; Ebrahim M. Songhori; Richard G. Baraniuk; Farinaz Koushanfar (IEEE Trans. Neural Networks Learn. Syst., 2018)

Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. - Daniel LeJeune; Reinhard Heckel; Richard G. Baraniuk (AISTATS, 2019)

IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. - Indu Manickam; Andrew S. Lan; Gautam Dasarathy; Richard G. Baraniuk (ASONAM, 2019)

A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading. - Zichao Wang 001; Andrew S. Lan; Andrew E. Waters; Phillip Grimaldi; Richard G. Baraniuk (EDM, 2019)

From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. - Randall Balestriero; Richard G. Baraniuk (ICLR (Poster), 2019)

Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks. - Joshua J. Michalenko; Ameesh Shah; Abhinav Verma 001; Richard G. Baraniuk; Swarat Chaudhuri; Ankit B. Patel (ICLR (Poster), 2019)

A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery. - Ali Mousavi 003; Gautam Dasarathy; Richard G. Baraniuk (ICLR (Poster), 2019)

A Max-Affine Spline Perspective of Recurrent Neural Networks. - Zichao Wang 001; Randall Balestriero; Richard G. Baraniuk (ICLR (Poster), 2019)

The Geometry of Deep Networks: Power Diagram Subdivision. - Randall Balestriero; Romain Cosentino; Behnaam Aazhang; Richard G. Baraniuk (NeurIPS, 2019)

RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data. - Benjamin Coleman; Anshumali Shrivastava; Richard G. Baraniuk (CoRR, 2019)

Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. - Daniel LeJeune; Richard G. Baraniuk; Reinhard Heckel (CoRR, 2019)

A Hessian Based Complexity Measure for Deep Networks. - Hamid Javadi; Randall Balestriero; Richard G. Baraniuk (CoRR, 2019)

Out-of-Distribution Detection Using Neural Rendering Generative Models. - Yujia Huang; Sihui Dai; Tan M. Nguyen; Richard G. Baraniuk; Anima Anandkumar (CoRR, 2019)

Drawing early-bird tickets: Towards more efficient training of deep networks. - Haoran You; Chaojian Li; Pengfei Xu 011; Yonggan Fu; Yue Wang 036; Xiaohan Chen; Yingyan Lin; Zhangyang Wang; Richard G. Baraniuk (CoRR, 2019)

InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers. - Tan M. Nguyen; Animesh Garg; Richard G. Baraniuk; Anima Anandkumar (CoRR, 2019)

Face Detection and Verification Using Lensless Cameras. - Jasper Tan; Li Niu 002; Jesse K. Adams; Vivek Boominathan; Jacob T. Robinson; Richard G. Baraniuk; Ashok Veeraraghavan (IEEE Trans. Computational Imaging, 2019)

Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform. - David Y. J. Kim; Adam Winchell; Andrew E. Waters; Phillip Grimaldi; Richard G. Baraniuk; Michael Mozer (iTextbooks@AIED, 2020)

Thresholding Graph Bandits with GrAPL. - Daniel LeJeune; Gautam Dasarathy; Richard G. Baraniuk (AISTATS, 2020)

The Implicit Regularization of Ordinary Least Squares Ensembles. - Daniel LeJeune; Hamid Javadi; Richard G. Baraniuk (AISTATS, 2020)

Attention Word Embedding. - Shashank Sonkar; Andrew E. Waters; Richard G. Baraniuk (COLING, 2020)

VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. - Zichao Wang 001; Yi Gu; Andrew S. Lan; Richard G. Baraniuk (EDM, 2020)

qDKT: Question-centric Deep Knowledge Tracing. - Shashank Sonkar; Andrew S. Lan; Andrew E. Waters; Phillip Grimaldi; Richard G. Baraniuk (EDM, 2020)

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. - Haoran You; Chaojian Li; Pengfei Xu 011; Yonggan Fu; Yue Wang 036; Xiaohan Chen; Richard G. Baraniuk; Zhangyang Wang; Yingyan Lin (ICLR, 2020)

CANOPIC: Pre-Digital Privacy-Enhancing Encodings for Computer Vision. - Jasper Tan; Salman Siddique Khan; Vivek Boominathan; Jeffrey Byrne; Richard G. Baraniuk; Kaushik Mitra; Ashok Veeraraghavan (ICME, 2020)

Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data. - Benjamin Coleman; Richard G. Baraniuk; Anshumali Shrivastava (ICML, 2020)

Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors. - Yehuda Dar; Paul M. Mayer; Lorenzo Luzi; Richard G. Baraniuk (ICML, 2020)

Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge. - Zichao Wang 001; Angus Lamb; Evgeny Saveliev; Pashmina Cameron; Yordan Zaykov; José Miguel Hernández-Lobato; Richard E. Turner; Richard G. Baraniuk; Craig Barton; Simon Peyton Jones; Simon Woodhead 002; Cheng Zhang 005 (NeurIPS (Competition and Demos), 2020)

Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks. - Randall Balestriero; Sébastien Paris; Richard G. Baraniuk (NeurIPS, 2020)

MomentumRNN: Integrating Momentum into Recurrent Neural Networks. - Tan M. Nguyen; Richard G. Baraniuk; Andrea L. Bertozzi; Stanley J. Osher; Bao Wang 001 (NeurIPS, 2020)

Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. - Bao Wang 001; Tan M. Nguyen; Andrea L. Bertozzi; Richard G. Baraniuk; Stanley J. Osher (CoRR, 2020)

Max-Affine Spline Insights into Deep Generative Networks. - Randall Balestriero; Sébastien Paris; Richard G. Baraniuk (CoRR, 2020)

An Improved Semi-Supervised VAE for Learning Disentangled Representations. - Weili Nie; Zichao Wang 001; Ankit B. Patel; Richard G. Baraniuk (CoRR, 2020)

Interpretable Super-Resolution via a Learned Time-Series Representation. - Randall Balestriero; Hervé Glotin; Richard G. Baraniuk (CoRR, 2020)

Analytical Probability Distributions and EM-Learning for Deep Generative Networks. - Randall Balestriero; Sébastien Paris; Richard G. Baraniuk (CoRR, 2020)

Ensembles of Generative Adversarial Networks for Disconnected Data. - Lorenzo Luzi; Randall Balestriero; Richard G. Baraniuk (CoRR, 2020)

Computer-Aided Personalized Education. - Rajeev Alur; Richard G. Baraniuk; Rastislav Bodík; Ann W. Drobnis; Sumit Gulwani; Bjoern Hartmann; Yasmin B. Kafai; Jeff Karpicke; Ran Libeskind-Hadas; Debra J. Richardson; Armando Solar-Lezama; Candace Thille; et al. (CoRR, 2020)

Diagnostic Questions: The NeurIPS 2020 Education Challenge. - Zichao Wang 001; Angus Lamb; Evgeny Saveliev; Pashmina Cameron; Yordan Zaykov; José Miguel Hernández-Lobato; Richard E. Turner; Richard G. Baraniuk; Craig Barton; Simon Peyton Jones; Simon Woodhead 002; Cheng Zhang 005 (CoRR, 2020)

Provable Finite Data Generalization with Group Autoencoder. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (CoRR, 2020)

Scalable Neural Tangent Kernel of Recurrent Architectures. - Sina Alemohammad; Randall Balestriero; Zichao Wang 001; Richard G. Baraniuk (CoRR, 2020)

Interpretable Image Clustering via Diffeomorphism-Aware K-Means. - Romain Cosentino; Randall Balestriero; Yanis Bahroun; Anirvan M. Sengupta; Richard G. Baraniuk; Behnaam Aazhang (CoRR, 2020)

Guest Editorial. - Richard G. Baraniuk; Alex Dimakis; Negar Kiyavash; Sewoong Oh; Rebecca Willett (IEEE J. Sel. Areas Inf. Theory, 2020)

Deep Learning Techniques for Inverse Problems in Imaging. - Gregory Ongie; Ajil Jalal; Christopher A. Metzler; Richard G. Baraniuk; Alexandros G. Dimakis; Rebecca Willett (IEEE J. Sel. Areas Inf. Theory, 2020)

Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. - Yue Wang 036; Jianghao Shen; Ting-Kuei Hu; Pengfei Xu 011; Tan M. Nguyen; Richard G. Baraniuk; Zhangyang Wang; Yingyan Lin (IEEE J. Sel. Top. Signal Process., 2020)

The science of deep learning. - Richard G. Baraniuk; David L. Donoho; Matan Gavish (Proc. Natl. Acad. Sci. USA, 2020)

Universal Frame Thresholding. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (IEEE Signal Process. Lett., 2020)

Inverse Scattering via Transmission Matrices: Broadband Illumination and Fast Phase Retrieval Algorithms. - Manoj Kumar Sharma; Christopher A. Metzler; Sudarshan Nagesh; Richard G. Baraniuk; Oliver Cossairt; Ashok Veeraraghavan (IEEE Trans. Computational Imaging, 2020)

Educational Question Mining At Scale: Prediction, Analysis and Personalization. - Zichao Wang 001; Sebastian Tschiatschek; Simon Woodhead 002; José Miguel Hernández-Lobato; Simon Peyton Jones; Richard G. Baraniuk; Cheng Zhang 005 (AAAI, 2021)

Mathematical Formula Representation via Tree Embeddings. - Zichao Wang 001; Andrew S. Lan; Richard G. Baraniuk (iTextbooks@AIED, 2021)

Towards Blooms Taxonomy Classification Without Labels. - Zichao Wang 001; Kyle Manning; Debshila Basu Mallick; Richard G. Baraniuk (AIED (1), 2021)

A Relationship Selection Task (short paper). - Andrew E. Waters; Vinay K. Chaudhri; Debshila Basu Mallick; Richard G. Baraniuk (iTextbooks@AIED, 2021)

A Case Study in Bootstrapping Ontology Graphs from Textbooks. - Vinay K. Chaudhri; Matthew Boggess; Han Lin Aung; Debshila Basu Mallick; Andrew C. Waters; Richard G. Baraniuk (AKBC, 2021)

Minipatch Learning as Implicit Ridge-Like Regularization. - Tianyi Yao; Daniel LeJeune; Hamid Javadi; Richard G. Baraniuk; Genevera I. Allen (BigComp, 2021)

Scientific Formula Retrieval via Tree Embeddings. - Zichao Wang 001; Mengxue Zhang; Richard G. Baraniuk; Andrew S. Lan (IEEE BigData, 2021)

Math Operation Embeddings for Open-ended Solution Analysis and Feedback. - Mengxue Zhang; Zichao Wang 001; Richard G. Baraniuk; Andrew S. Lan (EDM, 2021)

Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. - Zichao Wang 001; Andrew S. Lan; Richard G. Baraniuk (EMNLP (1), 2021)

Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. - Sina Alemohammad; Hossein Babaei; Randall Balestriero; Matt Y. Cheung; Ahmed Imtiaz Humayun; Daniel LeJeune; Naiming Liu; Lorenzo Luzi; Jasper Tan; Zichao Wang 001; Richard G. Baraniuk (ICASSP, 2021)

Thermal Image Processing via Physics-Inspired Deep Networks. - Vishwanath Saragadam; Akshat Dave; Ashok Veeraraghavan; Richard G. Baraniuk (ICCVW, 2021)

The Recurrent Neural Tangent Kernel. - Sina Alemohammad; Zichao Wang 001; Randall Balestriero; Richard G. Baraniuk (ICLR, 2021)

NePTuNe: Neural Powered Tucker Networkfor Knowledge Graph Completion. - Shashank Sonkar; Arzoo Katiyar; Richard G. Baraniuk (IJCKG, 2021)

Interpretable and Learnable Super-Resolution Time-Frequency Representation. - Randall Balestriero; Hervé Glotin; Richard G. Baraniuk (MSML, 2021)

Deep Autoencoders: From Understanding to Generalization Guarantees. - Romain Cosentino; Randall Balestriero; Richard G. Baraniuk; Behnaam Aazhang (MSML, 2021)

The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization. - Daniel LeJeune; Hamid Javadi; Richard G. Baraniuk (NeurIPS, 2021)

Max-Affine Spline Insights Into Deep Network Pruning. - Randall Balestriero; Haoran You; Zhihan Lu; Yutong Kou; Yingyan Lin; Richard G. Baraniuk (CoRR, 2021)

Transfer Learning Can Outperform the True Prior in Double Descent Regularization. - Yehuda Dar; Richard G. Baraniuk (CoRR, 2021)

Fast Jacobian-Vector Product for Deep Networks. - Randall Balestriero; Richard G. Baraniuk (CoRR, 2021)

NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion. - Shashank Sonkar; Arzoo Katiyar; Richard G. Baraniuk (CoRR, 2021)

Double Descent and Other Interpolation Phenomena in GANs. - Lorenzo Luzi; Yehuda Dar; Richard G. Baraniuk (CoRR, 2021)

A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning. - Yehuda Dar; Vidya Muthukumar; Richard G. Baraniuk (CoRR, 2021)

NeuroView: Explainable Deep Network Decision Making. - C. J. Barberan; Randall Balestriero; Richard G. Baraniuk (CoRR, 2021)

Transformer with a Mixture of Gaussian Keys. - Tam Nguyen; Tan M. Nguyen; Dung Le; Khuong Nguyen; Anh Tran; Richard G. Baraniuk; Nhat Ho; Stanley J. Osher (CoRR, 2021)

SASSI - Super-Pixelated Adaptive Spatio-Spectral Imaging. - Vishwanath Saragadam; Michael DeZeeuw; Richard G. Baraniuk; Ashok Veeraraghavan; Aswin C. Sankaranarayanan (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Mad Max: Affine Spline Insights Into Deep Learning. - Randall Balestriero; Richard G. Baraniuk (Proc. IEEE, 2021)

A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device. - Nathan Dunkelberger; Jennifer L. Sullivan; Joshua Bradley; Indu Manickam; Gautam Dasarathy; Richard G. Baraniuk; Marcia K. O'Malley (IEEE Trans. Haptics, 2021)

Spatial Transformer K-Means. - Romain Cosentino; Randall Balestriero; Yanis Bahroun; Anirvan M. Sengupta; Richard G. Baraniuk; Behnaam Aazhang (IEEECONF, 2022)

Automated Scoring for Reading Comprehension via In-context BERT Tuning. - Nigel Fernandez; Aritra Ghosh 001; Naiming Liu; Zichao Wang 001; Benoît Choffin; Richard G. Baraniuk; Andrew S. Lan (AIED (1), 2022)

Towards Human-Like Educational Question Generation with Large Language Models. - Zichao Wang 001; Jakob Valdez; Debshila Basu Mallick; Richard G. Baraniuk (AIED (1), 2022)

Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. - Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk (CVPR, 2022)

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. - Gowthami Somepalli; Liam Fowl; Arpit Bansal; Ping-Yeh Chiang; Yehuda Dar; Richard G. Baraniuk; Micah Goldblum; Tom Goldstein (CVPR, 2022)

MINER: Multiscale Implicit Neural Representation. - Vishwanath Saragadam; Jasper Tan; Guha Balakrishnan; Richard G. Baraniuk; Ashok Veeraraghavan (ECCV (23), 2022)

Open-ended Knowledge Tracing for Computer Science Education. - Naiming Liu; Zichao Wang 001; Richard G. Baraniuk; Andrew S. Lan (EMNLP, 2022)

NeuroView-RNN: It's About Time. - C. J. Barberan; Sina Alemmohammad; Naiming Liu; Randall Balestriero; Richard G. Baraniuk (FAccT, 2022)

NFT-K: Non-Fungible Tangent Kernels. - Sina Alemohammad; Hossein Babaei; C. J. Barberan; Naiming Liu; Lorenzo Luzi; Blake Mason; Richard G. Baraniuk (ICASSP, 2022)

DeepHull: Fast Convex Hull Approximation in High Dimensions. - Randall Balestriero; Zichao Wang 001; Richard G. Baraniuk (ICASSP, 2022)

Unrolling Particles: Unsupervised Learning of Sampling Distributions. - Fernando Gama; Nicolas Zilberstein; Richard G. Baraniuk; Santiago Segarra (ICASSP, 2022)

No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. - Ahmed Imtiaz Humayun; Randall Balestriero; Anastasios Kyrillidis; Richard G. Baraniuk (ICASSP, 2022)

MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. - Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk (ICLR, 2022)

Improving Transformers with Probabilistic Attention Keys. - Tam Minh Nguyen; Tan Minh Nguyen; Dung D. D. Le; Duy Khuong Nguyen; Viet-Anh Tran; Richard G. Baraniuk; Nhat Ho; Stanley J. Osher (ICML, 2022)

Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research. - Steven Ritter 001; Neil T. Heffernan; Joseph Jay Williams; Derek Lomas; Ben Motz; Debshila Basu Mallick; Klinton Bicknell; Danielle S. McNamara; René F. Kizilcec; Jeremy Roschelle; Richard G. Baraniuk; Ryan Baker 001 (L@S, 2022)

Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. - Tan Minh Nguyen; Richard G. Baraniuk; Robert M. Kirby; Stanley J. Osher; Bao Wang 001 (MSML, 2022)

Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. - Jasper Tan; Blake Mason; Hamid Javadi; Richard G. Baraniuk (NeurIPS, 2022)

Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer. - David J. Brenes; C. J. Barberan; Brady Hunt; Sonia G. Parra; Mila P. Salcedo; Júlio C. Possati-Resende; Miriam L. Cremer; Philip E. Castle; José H. T. G. Fregnani; Mauricio Maza; Kathleen M. Schmeler; Richard G. Baraniuk; et al. (Comput. Medical Imaging Graph., 2022)

MINER: Multiscale Implicit Neural Representations. - Vishwanath Saragadam; Jasper Tan; Guha Balakrishnan; Richard G. Baraniuk; Ashok Veeraraghavan (CoRR, 2022)

NeuroView-RNN: It's About Time. - C. J. Barberan; Sina Alemohammad; Naiming Liu; Randall Balestriero; Richard G. Baraniuk (CoRR, 2022)

Singular Value Perturbation and Deep Network Optimization. - Rudolf H. Riedi; Randall Balestriero; Richard G. Baraniuk (CoRR, 2022)

Open-Ended Knowledge Tracing. - Naiming Liu; Zichao Wang 001; Richard G. Baraniuk; Andrew S. Lan (CoRR, 2022)

Benign Overparameterization in Membership Inference with Early Stopping. - Jasper Tan; Daniel LeJeune; Blake Mason; Hamid Javadi; Richard G. Baraniuk (CoRR, 2022)

Batch Normalization Explained. - Randall Balestriero; Richard G. Baraniuk (CoRR, 2022)

A Visual Tour Of Current Challenges In Multimodal Language Models. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (CoRR, 2022)

Overfreezing Meets Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks. - Yehuda Dar; Lorenzo Luzi; Richard G. Baraniuk (CoRR, 2022)

Foveated Thermal Computational Imaging in the Wild Using All-Silicon Meta-Optics. - Vishwanath Saragadam; Zheyi Han; Vivek Boominathan; Luocheng Huang; Shiyu Tan; Johannes E. Fröch; Karl F. Böhringer; Richard G. Baraniuk; Arka Majumdar; Ashok Veeraraghavan (CoRR, 2022)

Uniform Partitioning of Data Grid for Association Detection. - Ali Mousavi 003; Richard G. Baraniuk (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent. - Bao Wang 001; Tan M. Nguyen; Tao Sun 005; Andrea L. Bertozzi; Richard G. Baraniuk; Stanley J. Osher (SIAM J. Imaging Sci., 2022)

Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting. - Ángel Bueno Rodríguez; Randall Balestriero; Silvio De Angelis; M. Carmen Benítez; Luciano Zuccarello; Richard G. Baraniuk; Jesús M. Ibáñez; Maarten V. de Hoop (IEEE Trans. Geosci. Remote. Sens., 2022)

Max-Affine Spline Insights Into Deep Network Pruning. - Haoran You; Randall Balestriero; Zhihan Lu; Yutong Kou; Huihong Shi; Shunyao Zhang; Shang Wu 003; Yingyan Lin; Richard G. Baraniuk (Trans. Mach. Learn. Res., 2022)

Extreme Compressed Sensing of Poisson Rates From Multiple Measurements. - Pavan K. Kota; Daniel LeJeune; Rebekah A. Drezek; Richard G. Baraniuk (IEEE Trans. Signal Process., 2022)

On Local Distributions in Graph Signal Processing. - T. Mitchell Roddenberry; Fernando Gama; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2022)

Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. - Yehuda Dar; Richard G. Baraniuk (SIAM J. Math. Data Sci., 2022)

Towards the Future of AI-Augmented Human Tutoring in Math Learning. - Vincent Aleven; Richard G. Baraniuk; Emma Brunskill; Scott A. Crossley; Dora Demszky; Stephen Fancsali; Shivang Gupta; Kenneth R. Koedinger; Chris Piech; Steven Ritter 001; Danielle R. Thomas; Simon Woodhead 002; et al. (AIED (Posters/Late Breaking Results/...), 2023)

A Case Study using Large Language Models to Generate Metadata for Math Questions. - Katie Bainbridge; Candace A. Walkington; Armon Ibrahim; Iris Zhong; Debshila Basu Mallick; Julianna Washington; Richard G. Baraniuk (LLM@AIED, 2023)

Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models. - Shashank Sonkar; Richard G. Baraniuk (LLM@AIED, 2023)

A Blessing of Dimensionality in Membership Inference through Regularization. - Jasper Tan; Daniel LeJeune; Blake Mason; Hamid Javadi; Richard G. Baraniuk (AISTATS, 2023)

MultiQG-TI: Towards Question Generation from Multi-modal Sources. - Zichao Wang 001; Richard G. Baraniuk (BEA@ACL, 2023)

SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. - Ahmed Imtiaz Humayun; Randall Balestriero; Guha Balakrishnan; Richard G. Baraniuk (CVPR, 2023)

WIRE: Wavelet Implicit Neural Representations. - Vishwanath Saragadam; Daniel LeJeune; Jasper Tan; Guha Balakrishnan; Ashok Veeraraghavan; Richard G. Baraniuk (CVPR, 2023)

CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. - Shashank Sonkar; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (EMNLP (Findings), 2023)

A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. - Tan M. Nguyen; Tam Nguyen; Long Bui; Hai Do; Duy Khuong Nguyen; Dung D. Le; Hung Tran-The; Nhat Ho; Stanley J. Osher; Richard G. Baraniuk (ICASSP, 2023)

Retrieval-based Controllable Molecule Generation. - Zichao Wang 001; Weili Nie; Zhuoran Qiao; Chaowei Xiao; Richard G. Baraniuk; Anima Anandkumar (ICLR, 2023)

A Primal-Dual Framework for Transformers and Neural Networks. - Tan Minh Nguyen; Tam Minh Nguyen; Nhat Ho; Andrea L. Bertozzi; Richard G. Baraniuk; Stanley J. Osher (ICLR, 2023)

Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. - Steven Ritter 001; Neil T. Heffernan; Joseph Jay Williams; Derek Lomas; Klinton Bicknell; Jeremy Roschelle; Ben Motz; Danielle S. McNamara; Richard G. Baraniuk; Debshila Basu Mallick; René F. Kizilcec; Ryan Baker 001; et al. (L@S, 2023)

Unlocking Financial Success: Empowering Higher Ed Students and Developing Financial Literacy Interventions at Scale. - Brittany C. Bradford; Debshila Basu Mallick; Richard G. Baraniuk (L@S, 2023)

Secure Education and Learning Research at Scale with OpenStax Kinetic. - Debshila Basu Mallick; Brittany C. Bradford; Richard G. Baraniuk (L@S, 2023)

Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. - Tam Nguyen; Tan Nguyen; Richard G. Baraniuk (NeurIPS, 2023)

MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages. - Shashank Sonkar; Zichao Wang 001; Richard G. Baraniuk (SustaiNLP, 2023)

Evaluating generative networks using Gaussian mixtures of image features. - Lorenzo Luzi; Carlos Ortiz Marrero; Nile Wynar; Richard G. Baraniuk; Michael J. Henry (WACV, 2023)

CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles. - Shashank Sonkar; Lucy Liu; Debshila Basu Mallick; Richard G. Baraniuk (CoRR, 2023)

Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net Design. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2023)

Deduction under Perturbed Evidence: Probing Student Simulation Capabilities of Large Language Models. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2023)

Novice Learner and Expert Tutor: Evaluating Math Reasoning Abilities of Large Language Models with Misconceptions. - Naiming Liu; Shashank Sonkar; Zichao Wang 001; Simon Woodhead 002; Richard G. Baraniuk (CoRR, 2023)

Training Dynamics of Deep Network Linear Regions. - Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk (CoRR, 2023)

Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals. - Tam Nguyen; Tan M. Nguyen; Richard G. Baraniuk (CoRR, 2023)

Perspectives on the State and Future of Deep Learning - 2023. - Micah Goldblum; Anima Anandkumar; Richard G. Baraniuk; Tom Goldstein; Kyunghyun Cho; Zachary C. Lipton; Melanie Mitchell; Preetum Nakkiran; Max Welling; Andrew Gordon Wilson (CoRR, 2023)

Unsupervised Learning of Sampling Distributions for Particle Filters. - Fernando Gama; Nicolas Zilberstein; Martin Sevilla; Richard G. Baraniuk; Santiago Segarra (IEEE Trans. Signal Process., 2023)

Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. - Shashank Sonkar; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (AIED (1), 2024)

Automated Long Answer Grading with RiceChem Dataset. - Shashank Sonkar; Kangqi Ni; Lesa Tran Lu; Kristi Kincaid; John S. Hutchinson; Richard G. Baraniuk (AIED (1), 2024)

Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (EMNLP (Findings), 2024)

MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. - Shashank Sonkar; Naiming Liu; Myco Le; Richard G. Baraniuk (EMNLP (Findings), 2024)

Pedagogical Alignment of Large Language Models. - Shashank Sonkar; Kangqi Ni; Sapana Chaudhary; Richard G. Baraniuk (EMNLP (Findings), 2024)

Titan: Bringing the Deep Image Prior to Implicit Representations. - Lorenzo Luzi; Daniel LeJeune; Ali Siahkoohi; Sina Alemohammad; Vishwanath Saragadam; Hossein Babaei; Naiming Liu; Zichao Wang 001; Richard G. Baraniuk (ICASSP, 2024)

Self-Consuming Generative Models Go MAD. - Sina Alemohammad; Josue Casco-Rodriguez; Lorenzo Luzi; Ahmed Imtiaz Humayun; Hossein Babaei; Daniel LeJeune; Ali Siahkoohi; Richard G. Baraniuk (ICLR, 2024)

Implicit Neural Representations and the Algebra of Complex Wavelets. - T. Mitchell Roddenberry; Vishwanath Saragadam; Maarten V. de Hoop; Richard G. Baraniuk (ICLR, 2024)

Deep Networks Always Grok and Here is Why. - Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk (ICML, 2024)

PIDformer: Transformer Meets Control Theory. - Tam Minh Nguyen; César A. Uribe; Tan Minh Nguyen; Richard G. Baraniuk (ICML, 2024)

Code Soliloquies for Accurate Calculations in Large Language Models. - Shashank Sonkar; Xinghe Chen; Myco Le; Naiming Liu; Debshila Basu Mallick; Richard G. Baraniuk (LAK, 2024)

Learning Transferable Features for Implicit Neural Representations. - Kushal Kardam Vyas; Ahmed Imtiaz Humayun; Aniket Dashpute; Richard G. Baraniuk; Ashok Veeraraghavan; Guha Balakrishnan (NeurIPS, 2024)

[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models. - Josue Casco-Rodriguez; Caleb Kemere; Richard G. Baraniuk (CoRR, 2024)

PIDformer: Transformer Meets Control Theory. - Tam Nguyen; César A. Uribe; Tan M. Nguyen; Richard G. Baraniuk (CoRR, 2024)

Regressive Side Effects of Training Language Models to Mimic Student Misconceptions. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (CoRR, 2024)

Many-Shot Regurgitation (MSR) Prompting. - Shashank Sonkar; Richard G. Baraniuk (CoRR, 2024)

Removing Bias from Maximum Likelihood Estimation with Model Autophagy. - Paul M. Mayer; Lorenzo Luzi; Ali Siahkoohi; Don H. Johnson; Richard G. Baraniuk (CoRR, 2024)

ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. - Omer Ronen; Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk; Bin Yu 001 (CoRR, 2024)

Synthetic Context Generation for Question Generation. - Naiming Liu; Zichao Wang 001; Richard G. Baraniuk (CoRR, 2024)

A Primal-Dual Framework for Transformers and Neural Networks. - Tan M. Nguyen; Tam Nguyen; Nhat Ho; Andrea L. Bertozzi; Richard G. Baraniuk; Stanley J. Osher (CoRR, 2024)

MalAlgoQA: A Pedagogical Approach for Evaluating Counterfactual Reasoning Abilities. - Naiming Liu; Shashank Sonkar; Myco Le; Richard G. Baraniuk (CoRR, 2024)

On the Geometry of Deep Learning. - Randall Balestriero; Ahmed Imtiaz Humayun; Richard G. Baraniuk (CoRR, 2024)

Self-Improving Diffusion Models with Synthetic Data. - Sina Alemohammad; Ahmed Imtiaz Humayun; Shruti Agarwal; John P. Collomosse; Richard G. Baraniuk (CoRR, 2024)

LLM-based Cognitive Models of Students with Misconceptions. - Shashank Sonkar; Xinghe Chen; Naiming Liu; Richard G. Baraniuk; Mrinmaya Sachan (CoRR, 2024)

MazeNet: An Accurate, Fast, and Scalable Deep Learning Solution for Steiner Minimum Trees. - Gabriel Díaz-Ramos; Toros Arikan; Richard G. Baraniuk (CoRR, 2024)

Atomic Learning Objectives Labeling: A High-Resolution Approach for Physics Education. - Naiming Liu; Shashank Sonkar; Debshila Basu Mallick; Richard G. Baraniuk; Zhongzhou Chen (CoRR, 2024)

The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. - Yehuda Dar; Daniel LeJeune; Richard G. Baraniuk (SIAM J. Math. Data Sci., 2024)

Boomerang: Local sampling on image manifolds using diffusion models. - Lorenzo Luzi; Paul M. Mayer; Josue Casco-Rodriguez; Ali Siahkoohi; Richard G. Baraniuk (Trans. Mach. Learn. Res., 2024)

Asymptotics of the Sketched Pseudoinverse. - Daniel LeJeune; Pratik Patil; Hamid Javadi; Richard G. Baraniuk; Ryan J. Tibshirani (SIAM J. Math. Data Sci., 2024)

Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust. - Hossein Babaei; Sina Alemohammad; Richard G. Baraniuk (IEEE Trans. Neural Networks Learn. Syst., 2024)

DeepTensor: Low-Rank Tensor Decomposition With Deep Network Priors. - Vishwanath Saragadam; Randall Balestriero; Ashok Veeraraghavan; Richard G. Baraniuk (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Do LLMs Make Mistakes Like Students? Exploring Natural Alignments Between Language Models and Human Error Patterns. - Naiming Liu; Shashank Sonkar; Richard G. Baraniuk (AIED (4), 2025)

Training LLM-Based Tutors to Improve Student Learning Outcomes in Dialogues. - Alexander Scarlatos; Naiming Liu; Jaewook Lee 006; Richard G. Baraniuk; Andrew S. Lan (AIED (1), 2025)

Many-Shot Regurgitation Prompting. - Shashank Sonkar; Naiming Liu; Richard G. Baraniuk (AIED (5), 2025)

Turing-Like Test for Personalized Educational AI. - Shashank Sonkar; Naiming Liu; Xinghe Chen; Richard G. Baraniuk (AIED (6), 2025)

Estimating the Number and Locations of Boundaries in Reverberant Environments with Deep Learning. - Toros Arikan; Luca M. Chackalackal; Fatima Ahsan; Konrad Tittel; Andrew C. Singer; Gregory W. Wornell; Richard G. Baraniuk (ICASSP, 2025)

Atomic Learning Objectives and LLMs Labeling: A High-Resolution Approach for Physics Education. - Naiming Liu; Shashank Sonkar; Debshila Basu Mallick; Richard G. Baraniuk; Zhongzhou Chen (LAK, 2025)

The Importance of Teaching Logic to Computer Scientists and Electrical Engineers. - Paul M. Mayer; Richard G. Baraniuk (ACM Trans. Comput. Educ., 2025)

The Imitation Game for Educational AI. - Shashank Sonkar; Naiming Liu; Xinghe Chen; Richard G. Baraniuk (CoRR, 2025)

Do LLMs Make Mistakes Like Students? Exploring Natural Alignment between Language Models and Human Error Patterns. - Naiming Liu; Shashank Sonkar; Richard G. Baraniuk (CoRR, 2025)

Improving Routing in Sparse Mixture of Experts with Graph of Tokens. - Tam Minh Nguyen; Ngoc N. Tran; Khai Nguyen; Richard G. Baraniuk (CoRR, 2025)

SaFARi: State-Space Models for Frame-Agnostic Representation. - Hossein Babaei; Mel White; Sina Alemohammad; Richard G. Baraniuk (CoRR, 2025)

WaLRUS: Wavelets for Long-range Representation Using SSMs. - Hossein Babaei; Mel White; Sina Alemohammad; Richard G. Baraniuk (CoRR, 2025)

W4S4: WaLRUS Meets S4 for Long-Range Sequence Modeling. - Hossein Babaei; Mel White; Richard G. Baraniuk (CoRR, 2025)

GrokAlign: Geometric Characterisation and Acceleration of Grokking. - Thomas Walker; Ahmed Imtiaz Humayun; Randall Balestriero; Richard G. Baraniuk (CoRR, 2025)

CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. - Naiming Liu; Richard G. Baraniuk; Shashank Sonkar (CoRR, 2025)