GrooveSim: a topography-accurate simulator for geographic routing in vehicular networks. - Rahul Mangharam; Daniel S. Weller; Daniel D. Stancil; Ragunathan Rajkumar; Jayendra S. Parikh (Vehicular Ad Hoc Networks, 2005)

GrooveNet: A Hybrid Simulator for Vehicle-to-Vehicle Networks. - Rahul Mangharam; Daniel S. Weller; Raj Rajkumar; Priyantha Mudalige; Fan Bai 002 (MobiQuitous, 2006)

Jitter compensation in sampling via polynomial least squares estimation. - Daniel S. Weller; Vivek K. Goyal (ICASSP, 2009)

Combined compressed sensing and parallel mri compared for uniform and random cartesian undersampling of K-space. - Daniel S. Weller; Jonathan R. Polimeni; Leo J. Grady; Lawrence L. Wald; Elfar Adalsteinsson; Vivek K. Goyal (ICASSP, 2011)

Evaluating sparsity penalty functions for combined compressed sensing and parallel MRI. - Daniel S. Weller; Jonathan R. Polimeni; Leo J. Grady; Lawrence L. Wald; Elfar Adalsteinsson; Vivek K. Goyal (ISBI, 2011)

On the Estimation of Nonrandom Signal Coefficients From Jittered Samples. - Daniel S. Weller; Vivek K. Goyal (IEEE Trans. Signal Process., 2011)

Bayesian Post-Processing Methods for Jitter Mitigation in Sampling. - Daniel S. Weller; Vivek K. Goyal (IEEE Trans. Signal Process., 2011)

Accelerated parallel magnetic resonance imaging reconstruction using joint estimation with a sparse signal model. - Daniel S. Weller; Jonathan R. Polimeni; Leo J. Grady; Lawrence L. Wald; Elfar Adalsteinsson; Vivek K. Goyal (SSP, 2012)

Accelerating MRI by unifying sparse models and multiple receivers. - Daniel S. Weller (2012)

Spoke pulse design in magnetic resonance imaging using greedy minimax algorithm. - Hao Sun; Daniel S. Weller; Alan Chu; Sathish Ramani; Daehyun Yoon; Jon-Fredrik Nielsen; Jeffrey A. Fessler (ISBI, 2013)

Sure-based parameter selection for parallel MRI reconstruction using GRAPPA and sparsity. - Daniel S. Weller; Sathish Ramani; Jon-Fredrik Nielsen; Jeffrey A. Fessler (ISBI, 2013)

Non-Cartesian MRI Reconstruction With Automatic Regularization Via Monte-Carlo SURE. - Sathish Ramani; Daniel S. Weller; Jon-Fredrik Nielsen; Jeffrey A. Fessler (IEEE Trans. Medical Imaging, 2013)

Sparsity-Promoting Calibration for GRAPPA Accelerated Parallel MRI Reconstruction. - Daniel S. Weller; Jonathan R. Polimeni; Leo J. Grady; Lawrence L. Wald; Elfar Adalsteinsson; Vivek K. Goyal (IEEE Trans. Medical Imaging, 2013)

Phase retrieval of sparse signals using optimization transfer and ADMM. - Daniel S. Weller; Ayelet Pnueli; Ori Radzyner; Gilad Divon; Yonina C. Eldar; Jeffrey A. Fessler (ICIP, 2014)

Augmented Lagrangian with Variable Splitting for Faster Non-Cartesian 𝕃1-SPIRiT MR Image Reconstruction. - Daniel S. Weller; Sathish Ramani; Jeffrey A. Fessler (IEEE Trans. Medical Imaging, 2014)

Regularization parameter trimming for iterative image reconstruction. - Haoyi Liang; Daniel S. Weller (ACSSC, 2015)

Undersampled Phase Retrieval With Outliers. - Daniel S. Weller; Ayelet Pnueli; Gilad Divon; Ori Radzyner; Yonina C. Eldar; Jeffrey A. Fessler (IEEE Trans. Computational Imaging, 2015)

Robust phase retrieval with sparsity under nonnegativity constraints. - Daniel S. Weller (ACSSC, 2016)

Denoising method selection by comparison-based image quality assessment. - Haoyi Liang; Daniel S. Weller (ICIP, 2016)

Edge-based texture granularity detection. - Haoyi Liang; Daniel S. Weller (ICIP, 2016)

Analysis-form sparse phase retrieval using variable-splitting. - Daniel S. Weller (SSIAI, 2016)

Reconstruction with dictionary learning for accelerated parallel magnetic resonance imaging. - Daniel S. Weller (SSIAI, 2016)

Comparison-based Image Quality Assessment for Parameter Selection. - Haoyi Liang; Daniel S. Weller (CoRR, 2016)

Comparison-Based Image Quality Assessment for Selecting Image Restoration Parameters. - Haoyi Liang; Daniel S. Weller (IEEE Trans. Image Process., 2016)

Whole brain reconstruction from multilayered sections of a mouse model of status epilepticus. - Haoyi Liang; Natalia Dabrowska; Jaideep Kapur; Daniel S. Weller (ACSSC, 2017)

Learning dictionaries for accelerated parallel MRI reconstruction. - Daniel S. Weller (CISS, 2017)

Content-aware neuron image enhancement. - Haoyi Liang; Scott T. Acton; Daniel S. Weller (ICIP, 2017)

Image quality affects deep learning reconstruction of MRI. - Haris Jeelani; Jonathan Martin; Francis Vasquez; Michael Salerno; Daniel S. Weller (ISBI, 2018)

Enhanced Center Coding for Cell Detection with Convolutional Neural Networks. - Haoyi Liang; Aijaz Naik; Cedric L. Williams; Jaideep Kapur; Daniel S. Weller (CoRR, 2019)

Real-time filtering with sparse variations for head motion in magnetic resonance imaging. - Daniel S. Weller; Douglas C. Noll; Jeffrey A. Fessler (Signal Process., 2019)

Content-Aware Enhancement of Images With Filamentous Structures. - Haris Jeelani; Haoyi Liang; Scott T. Acton; Daniel S. Weller (IEEE Trans. Image Process., 2019)

Structure-Based Intensity Propagation for 3-D Brain Reconstruction With Multilayer Section Microscopy. - Haoyi Liang; Natalia Dabrowska; Jaideep Kapur; Daniel S. Weller (IEEE Trans. Medical Imaging, 2019)

Hieroglyph: Hierarchical Glia Graph Skeletonization and Matching. - Tiffany T. Ly; Tamal Batabyal; Jeremy Thompson; Tajie H. Harris; Daniel S. Weller; Scott T. Acton (ACSSC, 2020)

VBET: Vesselness and Blob Enhancement Technique for 2d and 3d microscopy images of microglia. - Tanjin Taher Toma; Kanchan Bisht; Ukpong Eyo; Daniel S. Weller (ACSSC, 2020)

A Myocardial T1-Mapping Framework with Recurrent and U-Net Convolutional Neural Networks. - Haris Jeelani; Yang Yang 110; Ruixi Zhou; Christopher M. Kramer; Michael Salerno; Daniel S. Weller (ISBI, 2020)

Fast Automatic Parameter Selection for MRI Reconstruction. - Tanjin Taher Toma; Daniel S. Weller (ISBI, 2020)

Cellcounter: a deep learning framework for high-fidelity spatial localization of neurons. - Tamal Batabyal; Aijaz Ahmad Naik; Daniel S. Weller; Jaideep Kapur (CoRR, 2021)

Efficient Learning of Transform-Domain LMS Filter Using Graph Laplacian. - Tamal Batabyal; Daniel S. Weller; Jaideep Kapur; Scott T. Acton (IEEE Trans. Neural Networks Learn. Syst., 2023)