Pillow, Jonathan W.

47 publications

NeurIPS 2025 Efficient Training of Minimal and Maximal Low-Rank Recurrent Neural Networks Anushri Arora, Jonathan W. Pillow

NeurIPS 2025 Flexible Inference for Animal Learning Rules Using Neural Networks Yuhan Helena Liu, Victor Geadah, Jonathan W. Pillow

ICML 2025 Flow-Field Inference from Neural Data Using Deep Recurrent Networks Timothy Doyeon Kim, Thomas Zhihao Luo, Tankut Can, Kamesh Krishnamurthy, Jonathan W. Pillow, Carlos D Brody

NeurIPS 2025 Modeling Neural Activity with Conditionally Linear Dynamical Systems Victor Geadah, Amin Nejatbakhsh, David Lipshutz, Jonathan W. Pillow, Alex H Williams

NeurIPS 2024 Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems Aditi Jha, Diksha Gupta, Carlos D. Brody, Jonathan W. Pillow

ICLR 2024 Modeling State-Dependent Communication Between Brain Regions with Switching Nonlinear Dynamical Systems Orren Karniol-Tambour, David M. Zoltowski, E. Mika Diamanti, Lucas Pinto, Carlos D Brody, David W. Tank, Jonathan W. Pillow

ICLR 2024 Parsing Neural Dynamics with Infinite Recurrent Switching Linear Dynamical Systems Victor Geadah, International Brain Laboratory, Jonathan W. Pillow

TMLR 2023 Spectral Learning of Bernoulli Linear Dynamical Systems Models for Decision-Making Iris R Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow

NeurIPS 2022 Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior Zoe Ashwood, Aditi Jha, Jonathan W Pillow

NeurIPS 2022 Extracting Computational Mechanisms from Neural Data Using Low-Rank RNNs Adrian Valente, Jonathan W Pillow, Srdjan Ostojic

ICML 2021 Factor-Analytic Inverse Regression for High-Dimension, Small-Sample Dimensionality Reduction Aditi Jha, Michael J. Morais, Jonathan W Pillow

ICML 2021 Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations Timothy D. Kim, Thomas Z. Luo, Jonathan W. Pillow, Carlos D. Brody

NeurIPS 2020 High-Contrast “gaudy” Images Improve the Training of Deep Neural Network Models of Visual Cortex Benjamin Cowley, Jonathan W Pillow

NeurIPS 2020 Identifying Signal and Noise Structure in Neural Population Activity with Gaussian Process Factor Models Stephen Keeley, Mikio Aoi, Yiyi Yu, Spencer Smith, Jonathan W Pillow

NeurIPS 2020 Inferring Learning Rules from Animal Decision-Making Zoe Ashwood, Nicholas A. Roy, Ji Hyun Bak, Jonathan W Pillow

NeurIPS 2018 Efficient Inference for Time-Varying Behavior During Learning Nicholas A. Roy, Ji Hyun Bak, Athena Akrami, Carlos Brody, Jonathan W Pillow

NeurIPS 2018 Learning a Latent Manifold of Odor Representations from Neural Responses in Piriform Cortex Anqi Wu, Stan Pashkovski, Sandeep R Datta, Jonathan W Pillow

NeurIPS 2018 Model-Based Targeted Dimensionality Reduction for Neuronal Population Data Mikio Aoi, Jonathan W Pillow

NeurIPS 2018 Power-Law Efficient Neural Codes Provide General Link Between Perceptual Bias and Discriminability Michael Morais, Jonathan W Pillow

NeurIPS 2018 Scaling the Poisson GLM to Massive Neural Datasets Through Polynomial Approximations David Zoltowski, Jonathan W Pillow

NeurIPS 2017 Gaussian Process Based Nonlinear Latent Structure Discovery in Multivariate Spike Train Data Anqi Wu, Nicholas A. Roy, Stephen Keeley, Jonathan W Pillow

NeurIPS 2016 A Bayesian Method for Reducing Bias in Neural Representational Similarity Analysis Mingbo Cai, Nicolas W Schuck, Jonathan W Pillow, Yael Niv

NeurIPS 2016 Adaptive Optimal Training of Animal Behavior Ji Hyun Bak, Jung Yoon Choi, Athena Akrami, Ilana Witten, Jonathan W Pillow

NeurIPS 2016 Bayesian Latent Structure Discovery from Multi-Neuron Recordings Scott Linderman, Ryan P. Adams, Jonathan W Pillow

NeurIPS 2015 Convolutional Spike-Triggered Covariance Analysis for Neural Subunit Models Anqi Wu, ll Memming Park, Jonathan W Pillow

JMLR 2014 Bayesian Entropy Estimation for Countable Discrete Distributions Evan Archer, Il Memming Park, Jonathan W. Pillow

NeurIPS 2014 Inferring Sparse Representations of Continuous Signals with Continuous Orthogonal Matching Pursuit Karin C Knudson, Jacob Yates, Alexander Huk, Jonathan W Pillow

NeurIPS 2014 Inferring Synaptic Conductances from Spike Trains with a Biophysically Inspired Point Process Model Kenneth W Latimer, E. J. Chichilnisky, Fred Rieke, Jonathan W Pillow

NeurIPS 2014 Low-Dimensional Models of Neural Population Activity in Sensory Cortical Circuits Evan W Archer, Urs Koster, Jonathan W Pillow, Jakob H. Macke

NeurIPS 2014 Optimal Prior-Dependent Neural Population Codes Under Shared Input Noise Agnieszka Grabska-Barwinska, Jonathan W Pillow

NeurIPS 2014 Sparse Bayesian Structure Learning with “dependent Relevance Determination” Priors Anqi Wu, Mijung Park, Oluwasanmi O Koyejo, Jonathan W Pillow

NeurIPS 2013 Bayesian Entropy Estimation for Binary Spike Train Data Using Parametric Prior Knowledge Evan W Archer, ll Memming Park, Jonathan W Pillow

NeurIPS 2013 Bayesian Inference for Low Rank Spatiotemporal Neural Receptive Fields Mijung Park, Jonathan W Pillow

AISTATS 2013 Bayesian Structure Learning for Functional Neuroimaging Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow

NeurIPS 2013 Spectral Methods for Neural Characterization Using Generalized Quadratic Models ll Memming Park, Evan W Archer, Nicholas Priebe, Jonathan W Pillow

NeurIPS 2013 Spike Train Entropy-Rate Estimation Using Hierarchical Dirichlet Process Priors Karin C Knudson, Jonathan W Pillow

NeurIPS 2013 Universal Models for Binary Spike Patterns Using Centered Dirichlet Processes ll Memming Park, Evan W Archer, Kenneth Latimer, Jonathan W Pillow

NeurIPS 2012 Bayesian Active Learning with Localized Priors for Fast Receptive Field Characterization Mijung Park, Jonathan W. Pillow

NeurIPS 2012 Bayesian Estimation of Discrete Entropy with Mixtures of Stick-Breaking Priors Evan Archer, ll Memming Park, Jonathan W. Pillow

NeurIPS 2012 Fully Bayesian Inference for Neural Models with Negative-Binomial Spiking Jonathan W. Pillow, James Scott

NeurIPS 2011 Active Learning of Neural Response Functions with Gaussian Processes Mijung Park, Greg Horwitz, Jonathan W. Pillow

NeurIPS 2011 Bayesian Spike-Triggered Covariance Analysis ll Memming Park, Jonathan W. Pillow

NeurIPS 2009 Time-Rescaling Methods for the Estimation and Assessment of Non-Poisson Neural Encoding Models Jonathan W. Pillow

NeurIPS 2008 Characterizing Neural Dependencies with Copula Models Pietro Berkes, Frank Wood, Jonathan W. Pillow

NeurIPS 2007 Neural Characterization in Partially Observed Populations of Spiking Neurons Jonathan W. Pillow, Peter E. Latham

NeCo 2004 Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli

NeurIPS 2003 Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model Liam Paninski, Eero P. Simoncelli, Jonathan W. Pillow