Jonathan W. Pillow

According to our database, Jonathan W. Pillow authored at least 73 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Active Learning for Discrete Latent Variable Models.

Aditi Jha, Zoe C. Ashwood, Jonathan W. Pillow

Neural Comput., March, 2024

Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression.

C. Daniel Greenidge, Benjamin Scholl, Jacob L. Yates, Jonathan W. Pillow

Neural Comput., February, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Parsing neural dynamics with infinite recurrent switching linear dynamical systems.

Victor Geadah, International Brain Laboratory, Jonathan W. Pillow

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Scalable Variational Inference for Low-Rank Spatiotemporal Receptive Fields.

Lea Duncker, Kiersten M. Ruda, Greg D. Field, Jonathan W. Pillow

Neural Comput., June, 2023

Spectral learning of Bernoulli linear dynamical systems models for decision-making.

Iris R. Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow

Trans. Mach. Learn. Res., 2023

System Identification for Continuous-time Linear Dynamical Systems.

Peter Halmos, Jonathan W. Pillow, David A. Knowles

CoRR, 2023

2022

Correcting motion induced fluorescence artifacts in two-channel neural imaging.

Matthew S. Creamer, Kevin S. Chen, Andrew M. Leifer, Jonathan W. Pillow

PLoS Comput. Biol., September, 2022

Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models.

Adrian Valente, Srdjan Ostojic, Jonathan W. Pillow

Neural Comput., 2022

Bayesian Active Learning for Discrete Latent Variable Models.

Aditi Jha, Zoe C. Ashwood, Jonathan W. Pillow

CoRR, 2022

Loss-calibrated expectation propagation for approximate Bayesian decision-making.

Michael J. Morais, Jonathan W. Pillow

CoRR, 2022

Extracting computational mechanisms from neural data using low-rank RNNs.

Adrian Valente, Jonathan W. Pillow, Srdjan Ostojic

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior.

Zoe Ashwood, Aditi Jha, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Brain kernel: A new spatial covariance function for fMRI data.

Anqi Wu, Samuel A. Nastase, Christopher Baldassano, Nicholas B. Turk-Browne, Kenneth A. Norman, Barbara E. Engelhardt, Jonathan W. Pillow

NeuroImage, 2021

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity.

Felix Pei, Joel Ye, David M. Zoltowski, Anqi Wu, Raeed H. Chowdhury, Hansem Sohn, Joseph E. O'Doherty, Krishna V. Shenoy, Matthew T. Kaufman, Mark M. Churchland, Mehrdad Jazayeri, Lee E. Miller, Jonathan W. Pillow, Il Memming Park, Eva L. Dyer, Chethan Pandarinath

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations.

Timothy D. Kim, Thomas Z. Luo, Jonathan W. Pillow, Carlos D. Brody

Proceedings of the 38th International Conference on Machine Learning, 2021

Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction.

Aditi Jha, Michael J. Morais, Jonathan W. Pillow

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Poisson balanced spiking networks.

Camille E. Rullán Buxó, Jonathan W. Pillow

PLoS Comput. Biol., 2020

Identifying signal and noise structure in neural population activity with Gaussian process factor models.

Stephen L. Keeley, Mikio C. Aoi, Yiyi Yu, Spencer L. Smith, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Inferring learning rules from animal decision-making.

Zoe Ashwood, Nicholas A. Roy, Ji Hyun Bak, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

High-contrast "gaudy" images improve the training of deep neural network models of visual cortex.

Benjamin Cowley, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A general recurrent state space framework for modeling neural dynamics during decision-making.

David M. Zoltowski, Jonathan W. Pillow, Scott W. Linderman

Proceedings of the 37th International Conference on Machine Learning, 2020

Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations.

Stephen L. Keeley, David M. Zoltowski, Yiyi Yu, Spencer L. Smith, Jonathan W. Pillow

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias.

Mingbo Cai, Nicolas W. Schuck, Jonathan W. Pillow, Yael Niv

PLoS Comput. Biol., 2019

Dependent relevance determination for smooth and structured sparse regression.

Anqi Wu, Oluwasanmi Koyejo, Jonathan W. Pillow

J. Mach. Learn. Res., 2019

Fast shared response model for fMRI data.

Hugo Richard, Lucas Martin, Ana Luísa Pinho, Jonathan W. Pillow, Bertrand Thirion

CoRR, 2019

Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations.

Stephen L. Keeley, David M. Zoltowski, Yiyi Yu, Jacob L. Yates, Spencer L. Smith, Jonathan W. Pillow

CoRR, 2019

2018

Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability.

Adam S. Charles, Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow

Neural Comput., 2018

Shared Representational Geometry Across Neural Networks.

Qihong Lu, Po-Hsuan Chen, Jonathan W. Pillow, Peter J. Ramadge, Kenneth A. Norman, Uri Hasson

CoRR, 2018

Scaling the Poisson GLM to massive neural datasets through polynomial approximations.

David M. Zoltowski, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning a latent manifold of odor representations from neural responses in piriform cortex.

Anqi Wu, Stan L. Pashkovski, Sandeep R. Datta, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Efficient inference for time-varying behavior during learning.

Nicholas A. Roy, Ji Hyun Bak, Athena Akrami, Carlos D. Brody, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Power-law efficient neural codes provide general link between perceptual bias and discriminability.

Michael J. Morais, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Model-based targeted dimensionality reduction for neuronal population data.

Mikio C. Aoi, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models.

Alison I. Weber, Jonathan W. Pillow

Neural Comput., 2017

Gaussian process based nonlinear latent structure discovery in multivariate spike train data.

Anqi Wu, Nicholas A. Roy, Stephen L. Keeley, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Stochastic filtering of two-photon imaging using reweighted ℓ1.

Adam S. Charles, Alexander Song, Sue Ann Koay, David W. Tank, Jonathan W. Pillow

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Bayesian latent structure discovery from multi-neuron recordings.

Scott W. Linderman, Ryan P. Adams, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Bayesian method for reducing bias in neural representational similarity analysis.

Mingbo Cai, Nicolas W. Schuck, Jonathan W. Pillow, Yael Niv

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Adaptive optimal training of animal behavior.

Ji Hyun Bak, Jung Choi, Ilana Witten, Athena Akrami, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction.

Ross S. Williamson, Maneesh Sahani, Jonathan W. Pillow

PLoS Comput. Biol., 2015

Convolutional spike-triggered covariance analysis for neural subunit models.

Anqi Wu, Il Memming Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Bayesian Active Learning of Neural Firing Rate Maps with Transformed Gaussian Process Priors.

Mijung Park, J. Patrick Weller, Gregory D. Horwitz, Jonathan W. Pillow

Neural Comput., 2014

Bayesian entropy estimation for countable discrete distributions.

Evan Archer, Il Memming Park, Jonathan W. Pillow

J. Mach. Learn. Res., 2014

Sparse Bayesian structure learning with dependent relevance determination priors.

Anqi Wu, Mijung Park, Oluwasanmi Koyejo, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 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

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit.

Karin C. Knudson, Jacob L. Yates, Alexander Huk, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Optimal prior-dependent neural population codes under shared input noise.

Agnieszka Grabska-Barwinska, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Low-dimensional models of neural population activity in sensory cortical circuits.

Evan W. Archer, Urs Köster, Jonathan W. Pillow, Jakob H. Macke

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Bayesian and Quasi-Bayesian Estimators for Mutual Information from Discrete Data.

Evan Archer, Il Memming Park, Jonathan W. Pillow

Entropy, 2013

Bayesian inference for low rank spatiotemporal neural receptive fields.

Mijung Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Spectral methods for neural characterization using generalized quadratic models.

Il Memming Park, Evan Archer, Nicholas Priebe, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Universal models for binary spike patterns using centered Dirichlet processes.

Il Memming Park, Evan Archer, Kenneth W. Latimer, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Spike train entropy-rate estimation using hierarchical Dirichlet process priors.

Karin C. Knudson, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Bayesian entropy estimation for binary spike train data using parametric prior knowledge.

Evan Archer, Il Memming Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Bayesian Structure Learning for Functional Neuroimaging.

Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells.

Michael Vidne, Yashar Ahmadian, Jonathon Shlens, Jonathan W. Pillow, Jayant Kulkarni, Alan M. Litke, E. J. Chichilnisky, Eero P. Simoncelli, Liam Paninski

J. Comput. Neurosci., 2012

Fully Bayesian inference for neural models with negative-binomial spiking.

Jonathan W. Pillow, James G. Scott

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Bayesian active learning with localized priors for fast receptive field characterization.

Mijung Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Bayesian estimation of discrete entropy with mixtures of stick-breaking priors.

Evan Archer, Il Memming Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Receptive Field Inference with Localized Priors.

Mijung Park, Jonathan W. Pillow

PLoS Comput. Biol., 2011

Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains.

Jonathan W. Pillow, Yashar Ahmadian, Liam Paninski

Neural Comput., 2011

Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains.

Yashar Ahmadian, Jonathan W. Pillow, Liam Paninski

Neural Comput., 2011

Bayesian Spike-Triggered Covariance Analysis.

Il Memming Park, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Active learning of neural response functions with Gaussian processes.

Mijung Park, Greg Horwitz, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2009

Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models.

Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008

Characterizing neural dependencies with copula models.

Pietro Berkes, Frank D. Wood, Jonathan W. Pillow

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Neural characterization in partially observed populations of spiking neurons.

Jonathan W. Pillow, Peter E. Latham

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005

Comparing integrate-and-fire models estimated using intracellular and extracellular data.

Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli

Neurocomputing, 2005

2004

Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model.

Liam Paninski, Jonathan W. Pillow, Eero P. Simoncelli

Neural Comput., 2004

2003

Biases in white noise analysis due to non-Poisson spike generation.

Jonathan W. Pillow, Eero P. Simoncelli

Neurocomputing, 2003

Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model.

Jonathan W. Pillow, Liam Paninski, Eero P. Simoncelli

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2000

Encoding multiple orientations in a recurrent network.

Richard S. Zemel, Jonathan W. Pillow

Neurocomputing, 2000