A Mathematical Model of the Cerebellar-Olivary System I: Self-Regulating Equilibrium of Climbing Fiber Activity. - Garrett T. Kenyon; Javier F. Medina; Michael D. Mauk (J. Comput. Neurosci., 1998)

A Mathematical Model of the Cerebellar-Olivary System II: Motor Adaptation Through Systematic Disruption of Climbing Fiber Equilibrium. - Garrett T. Kenyon; Javier F. Medina; Michael D. Mauk (J. Comput. Neurosci., 1998)

Dynamic imaging of brain function: toward convergence with neural network simulation. - John S. George; D. Rector; Garrett T. Kenyon; David M. Schmidt 004; Bryan J. Travis; C. C. Wood (ISBI, 2002)

Firing correlations improve detection of moving bars. - Garrett T. Kenyon; James Theiler; David W. Marshak; Bartlett Moore; Janelle Jeffs; Bryan J. Travis (IJCNN, 2003)

Role of synaptic feedback and intrinsic voltage-gated currents in shaping cone light responses. - Garrett T. Kenyon; Bryan J. Travis; David W. Marshak (Neurocomputing, 2003)

Neurally-Based Algorithms for Image Processing. - Mark Flynn; Henry D. I. Abarbanel; Garrett T. Kenyon (AIPR, 2004)

Unsupervised Adaptation to Improve Fault Tolerance of Neural Network Classifiers. - Alex Nugent; Garrett T. Kenyon; Reid B. Porter (Evolvable Hardware, 2004)

Correlated Firing Improves Stimulus Discrimination in a Retinal Model. - Garrett T. Kenyon; James Theiler; John S. George; Bryan J. Travis; David W. Marshak (Neural Comput., 2004)

A theory of the Benham Top based on center-surround interactions in the parvocellular pathway. - Garrett T. Kenyon; Dan Hill; James Theiler; John S. George; David W. Marshak (Neural Networks, 2004)

Stimulus-specific oscillations in a retinal model. - Garrett T. Kenyon; Bryan J. Travis; James Theiler; John S. George; Greg J. Stephens; David W. Marshak (IEEE Trans. Neural Networks, 2004)

Time-to-Collision Estimation from Motion Based on Primate Visual Processing. - John M. Galbraith; Garrett T. Kenyon; Richard W. Ziolkowski (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

See globally, spike locally: oscillations in a retinal model encode large visual features. - Greg J. Stephens; Sergio Neuenschwander; John S. George; Wolf Singer; Garrett T. Kenyon (Biol. Cybern., 2006)

A reconfigurable computing framework for multi-scale cellular image processing. - Reid B. Porter; Jan R. Frigo; Al Conti; Neal R. Harvey; Garrett T. Kenyon; Maya B. Gokhale (Microprocess. Microsystems, 2007)

Extracting Number-Selective Responses from Coherent Oscillations in a Computer Model. - Jeremy A. Miller; Garrett T. Kenyon (Neural Comput., 2007)

Cellular Automata for Distributed Sensor Networks. - Dylan G. Allegretti; Garrett T. Kenyon; William C. Priedhorsky (Int. J. High Perform. Comput. Appl., 2008)

Large-scale functional models of visual cortex for remote sensing. - Steven P. Brumby; Garrett T. Kenyon; Will Landecker; Craig Rasmussen; Sriram Swaminarayan; Luís M. A. Bettencourt (AIPR, 2009)

Asymmetry and Similarity Phenomena in Backwards Masking Experiments Suggest Internal Reconstruction. - Tsvi Achler; Luís M. A. Bettencourt; Garrett T. Kenyon (CogSci, 2011)

Hierarchical discriminative sparse coding via bidirectional connections. - Zhengping Ji; Wentao Huang; Garrett T. Kenyon; Luís M. A. Bettencourt (IJCNN, 2011)

Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception. - Vadas Gintautas; Michael I. Ham; Benjamin Kunsberg; Shawn Barr; Steven P. Brumby; Craig Rasmussen; John S. George; Ilya Nemenman; Luís M. A. Bettencourt; Garrett T. Kenyon (PLoS Comput. Biol., 2011)

Development of invariant feature maps via a computational model of simple and complex cells. - Wentao Huang; Zhengping Ji; Steven P. Brumby; Garrett T. Kenyon; Luís M. A. Bettencourt (IJCNN, 2012)

Combining multiple visual processing streams for locating and classifying objects in video. - Dylan M. Paiton; Steven P. Brumby; Garrett T. Kenyon; Gerd J. Kunde; Kris D. Peterson; Mohammed I. Ham; Peter F. Schultz; John S. George (SSIAI, 2012)

A symmetry-breaking generative model of a simple-cell/complex-cell hierarchy. - Peter F. Schultz; Luís M. A. Bettencourt; Garrett T. Kenyon (SSIAI, 2012)

Interpreting individual classifications of hierarchical networks. - Will Landecker; Michael D. Thomure; Luís M. A. Bettencourt; Melanie Mitchell; Garrett T. Kenyon; Steven P. Brumby (CIDM, 2013)

Biologically inspired distributed sensor networks: Collective signal amplification via ultra-low bandwidth spike-based communication. - Sheng Y. Lundquist; Dylan M. Paiton; Brennan M. Nowers; Peter F. Schultz; Steven P. Brumby; Anders M. Jorgensen; Garrett T. Kenyon (IJCNN, 2013)

On the role of shape prototypes in hierarchical models of vision. - Michael D. Thomure; Melanie Mitchell; Garrett T. Kenyon (IJCNN, 2013)

Replicating Kernels with a Short Stride Allows Sparse Reconstructions with Fewer Independent Kernels. - Peter F. Schultz; Dylan M. Paiton; Wei Lu; Garrett T. Kenyon (CoRR, 2014)

A Deconvolutional Competitive Algorithm for Building Sparse Hierarchical Representations. - Dylan M. Paiton; Sheng Y. Lundquist; William Shainin; Xinhua Zhang; Peter F. Schultz; Garrett T. Kenyon (BICT, 2015)

A Deconvolutional Strategy for Implementing Large Patch Sizes Supports Improved Image Classification. - Xinhua Zhang; Garrett T. Kenyon (BICT, 2015)

Learning phase-rich features from streaming auditory images. - Mohit L. Dubey; Peter F. Schultz; Garrett T. Kenyon (SSIAI, 2016)

Sparse encoding of binocular images for depth inference. - Sheng Y. Lundquist; Dylan M. Paiton; Peter F. Schultz; Garrett T. Kenyon (SSIAI, 2016)

Efficient Distributed Semi-Supervised Learning using Stochastic Regularization over Affinity Graphs. - Sunil Thulasidasan; Jeffrey A. Bilmes; Garrett T. Kenyon (CoRR, 2016)

Generating Sparse Representations Using Quantum Annealing: Comparison to Classical Algorithms. - Nga T. T. Nguyen; Amy E. Larson; Garrett T. Kenyon (ICRC, 2017)

Sparse Coding on Stereo Video for Object Detection. - Sheng Y. Lundquist; Melanie Mitchell; Garrett T. Kenyon (CoRR, 2017)

Phase Transitions in Image Denoising via Sparsely Coding Convolutional Neural Networks. - Jacob Carroll; Nils Carlson; Garrett T. Kenyon (CoRR, 2017)

Does Phase Matter For Monaural Source Separation? - Mohit L. Dubey; Garrett T. Kenyon; Nils Carlson; Austin Thresher (CoRR, 2017)

Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons. - Edward Kim 006; Darryl Hannan; Garrett T. Kenyon (CVPR, 2018)

Image Classification Using Quantum Inference on the D-Wave 2X. - Nga T. T. Nguyen; Garrett T. Kenyon (ICRC, 2018)

Radiographic Inference Based on a Model of V1 Simple Cells Implemented on the D-Wave 2X Quantum Annealing Computer. - Nga T. T. Nguyen; Garrett T. Kenyon (ICRC, 2018)

Can Deep Learning Learn the Principle of Closed Contour Detection? - Xinhua Zhang; Yijing Watkins; Garrett T. Kenyon (ISVC, 2018)

Image Compression: Sparse Coding vs. Bottleneck Autoencoders. - Yijing Watkins; Oleksandr Iaroshenko; Mohammad Sayeh; Garrett T. Kenyon (SSIAI, 2018)

Sparse coding of pathology slides compared to transfer learning with deep neural networks. - Will Fischer 001; Sanketh S. Moudgalya; Judith D. Cohn; Nga T. T. Nguyen; Garrett T. Kenyon (BMC Bioinform., 2018)

Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples. - Jacob M. Springer; Charles M. S. Strauss; Austin M. Thresher; Edward Kim 006; Garrett T. Kenyon (CoRR, 2018)

Separating musical sources with convolutional sparse coding. - Mohit L. Dubey; Haydn Thomas Jones; Austin Thresher; Garrett T. Kenyon (APPIS, 2019)

A Neuromorphic Sparse Coding Defense to Adversarial Images. - Edward Kim 006; Jessica Yarnall; Priya Shah; Garrett T. Kenyon (ICONS, 2019)

Unsupervised Dictionary Learning via a Spiking Locally Competitive Algorithm. - Yijing Watkins; Austin Thresher; Peter F. Schultz; Andreas Wild; Andrew Sornborger; Garrett T. Kenyon (ICONS, 2019)

Using models of cortical development based on sparse coding to discriminate between real and synthetically-generated faces. - Nga T. T. Nguyen; Juston S. Moore; Garrett T. Kenyon (AIPR, 2020)

Modeling Biological Immunity to Adversarial Examples. - Edward Kim 006; Jocelyn Rego; Yijing Watkins; Garrett T. Kenyon (CVPR, 2020)

Using Sinusoidally-Modulated Noise as a Surrogate for Slow-Wave Sleep to Accomplish Stable Unsupervised Dictionary Learning in a Spike-Based Sparse Coding Model. - Yijing Watkins; Edward Kim 006; Andrew Sornborger; Garrett T. Kenyon (CVPR Workshops, 2020)

Alien vs. Predator: Brain Inspired Sparse Coding Optimization on Neuromorphic and Quantum Devices. - Kyle Henke; Ben Migliori; Garrett T. Kenyon (ICRC, 2020)

Machine Learning in a Post Moore's Law World: Quantum vs. Neuromorphic Substrates. - Kyle Henke; Garrett T. Kenyon; Ben Migliori (SSIAI, 2020)

Can Lateral Inhibition for Sparse Coding Help Explain V1 Neuronal Responses To Natural Stimuli? - Michael A. Teti; Emily Meyer; Garrett T. Kenyon (SSIAI, 2020)

Sparse MP4. - Daniel A. Wang; Charles M. S. Strauss; Jacob M. Springer; Austin Thresher; Howard Pritchard; Garrett T. Kenyon (SSIAI, 2020)

It's Hard for Neural Networks to Learn the Game of Life. - Jacob M. Springer; Garrett T. Kenyon (IJCNN, 2021)

A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (NeurIPS, 2021)

Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (CoRR, 2021)

A Little Robustness Goes a Long Way: Leveraging Universal Features for Targeted Transfer Attacks. - Jacob M. Springer; Melanie Mitchell; Garrett T. Kenyon (CoRR, 2021)

Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer. - Boram Yoon; Chia-Cheng Chang; Garrett T. Kenyon; Nga T. T. Nguyen; Ermal Rrapaj (CoRR, 2021)

On visual self-supervision and its effect on model robustness. - Michal Kucer; Diane Oyen; Garrett T. Kenyon (CoRR, 2021)

LCANets: Lateral Competition Improves Robustness Against Corruption and Attack. - Michael A. Teti; Garrett T. Kenyon; Ben Migliori; Juston Moore (ICML, 2022)

Apples-to-spikes: The first detailed comparison of LASSO solutions generated by a spiking neuromorphic processor. - Kyle Henke; Michael A. Teti; Garrett T. Kenyon; Ben Migliori; Gerd J. Kunde (ICONS, 2022)

Think Fast: Time Control in Varying Paradigms of Spiking Neural Networks. - Steven C. Nesbit; Andrew O'Brien 002; Jocelyn Rego; Gavin Parpart; Carlos González Rivera; Garrett T. Kenyon; Edward Kim 006; Terrence C. Stewart; Yijing Watkins (ICONS, 2022)

Dictionary Learning with Accumulator Neurons. - Gavin Parpart; Carlos González Rivera; Terrence C. Stewart; Edward Kim 006; Jocelyn Rego; Andrew O'Brien 002; Steven C. Nesbit; Garrett T. Kenyon; Yijing Watkins (ICONS, 2022)

Sparse Kernel Transfer Learning. - Edward Kim 006; Trang Ha; Garrett T. Kenyon (ISVC (2), 2022)

If you've trained one you've trained them all: inter-architecture similarity increases with robustness. - Haydn Thomas Jones; Jacob M. Springer; Garrett T. Kenyon; Juston S. Moore (UAI, 2022)

Fast Post-Hoc Normalization for Brain Inspired Sparse Coding on a Neuromorphic Device. - Kyle Henke; Garrett T. Kenyon; Ben Migliori (IEEE Trans. Parallel Distributed Syst., 2022)

A review of non-cognitive applications for neuromorphic computing. - James B. Aimone; Prasanna Date; Gabriel A. Fonseca Guerra; Kathleen E. Hamilton; Kyle Henke; Bill Kay; Garrett T. Kenyon; Shruti R. Kulkarni; Susan M. Mniszewski; Maryam Parsa; Sumedh R. Risbud; Catherine D. Schuman; et al. (Neuromorph. Comput. Eng., 2022)

Sampling binary sparse coding QUBO models using a spiking neuromorphic processor. - Kyle Henke; Elijah Pelofske; Georg Hahn; Garrett T. Kenyon (ICONS, 2023)

Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor. - Gavin Parpart; Sumedh R. Risbud; Garrett T. Kenyon; Yijing Watkins (ICONS, 2023)

An Interface-Type Memristive Device for Artificial Synapse and Neuromorphic Computing. - Sundar Kunwar; Zachary Jernigan; Zach Hughes; Chase Somodi; Michael Saccone; Francesco Caravelli; Pinku Roy; Di Zhang; Haiyan Wang; Quanxi Jia; Judith L. MacManus-Driscoll; Garrett T. Kenyon; et al. (Adv. Intell. Syst., 2023)

An Interface-Type Memristive Device for Artificial Synapse and Neuromorphic Computing. - Sundar Kunwar; Zachary Jernigan; Zach Hughes; Chase Somodi; Michael D. Saccone; Francesco Caravelli; Pinku Roy; Di Zhang; Haiyan Wang; Quanxi Jia; Judith L. MacManus-Driscoll; Garrett T. Kenyon; et al. (Adv. Intell. Syst., 2023)

The Selectivity and Competition of the Mind's Eye in Visual Perception. - Edward Kim 006; Maryam Daniali; Jocelyn Rego; Garrett T. Kenyon (ICASSP, 2024)

LCANets++: Robust Audio Classification Using Multi-Layer Neural Networks with Lateral Competition. - Sayanton V. Dibbo; Juston S. Moore; Garrett T. Kenyon; Michael A. Teti (ICASSP Workshops, 2024)

Energy-Based Models Trained with Equilibrium Propagation are Inherently Robust. - Siddharth Mansingh; Michal Kucer; Garrett T. Kenyon; Juston Moore; Michael A. Teti (ICMLA, 2024)

Event-To-Video Conversion for Overhead Object Detection. - Darryl Hannan; Ragib Arnab; Gavin Parpart; Garrett T. Kenyon; Edward Kim 006; Yijing Watkins (SSIAI, 2024)

How Robust Are Energy-Based Models Trained With Equilibrium Propagation? - Siddharth Mansingh; Michal Kucer; Garrett T. Kenyon; Juston Moore; Michael A. Teti (CoRR, 2024)

Comparing Quantum Annealing and Spiking Neuromorphic Computing for Sampling Binary Sparse Coding QUBO Problems. - Kyle Henke; Elijah Pelofske; Garrett T. Kenyon; Georg Hahn (CoRR, 2024)

Demonstrating the Suitability of Neuromorphic, Event-Based, Dynamic Vision Sensors for In Process Monitoring of Metallic Additive Manufacturing and Welding. - David Mascareñas; Andre Green; Ashlee S. Liao; Michael Torrez; Alessandro Cattaneo; Amber Black; John Bernardin; Garrett T. Kenyon (CoRR, 2024)