Jonathan W Pillow

Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems NeurIPS 2024 Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior NeurIPS 2022 Extracting computational mechanisms from neural data using low-rank RNNs NeurIPS 2022 Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction ICML 2021 High-contrast “gaudy” images improve the training of deep neural network models of visual cortex NeurIPS 2020 Identifying signal and noise structure in neural population activity with Gaussian process factor models NeurIPS 2020 Inferring learning rules from animal decision-making NeurIPS 2020 Efficient inference for time-varying behavior during learning NeurIPS 2018 Learning a latent manifold of odor representations from neural responses in piriform cortex NeurIPS 2018 Model-based targeted dimensionality reduction for neuronal population data NeurIPS 2018 Power-law efficient neural codes provide general link between perceptual bias and discriminability NeurIPS 2018 Scaling the Poisson GLM to massive neural datasets through polynomial approximations NeurIPS 2018 Gaussian process based nonlinear latent structure discovery in multivariate spike train data NeurIPS 2017 A Bayesian method for reducing bias in neural representational similarity analysis NeurIPS 2016 Adaptive optimal training of animal behavior NeurIPS 2016 Bayesian latent structure discovery from multi-neuron recordings NeurIPS 2016 Convolutional spike-triggered covariance analysis for neural subunit models NeurIPS 2015 Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit NeurIPS 2014 Inferring synaptic conductances from spike trains with a biophysically inspired point process model NeurIPS 2014 Low-dimensional models of neural population activity in sensory cortical circuits NeurIPS 2014 Optimal prior-dependent neural population codes under shared input noise NeurIPS 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Bayesian entropy estimation for binary spike train data using parametric prior knowledge NeurIPS 2013 Bayesian inference for low rank spatiotemporal neural receptive fields NeurIPS 2013 Spectral methods for neural characterization using generalized quadratic models NeurIPS 2013 Spike train entropy-rate estimation using hierarchical Dirichlet process priors NeurIPS 2013 Universal models for binary spike patterns using centered Dirichlet processes NeurIPS 2013 Bayesian active learning with localized priors for fast receptive field characterization NeurIPS 2012 Bayesian estimation of discrete entropy with mixtures of stick-breaking priors NeurIPS 2012 Fully Bayesian inference for neural models with negative-binomial spiking NeurIPS 2012 Active learning of neural response functions with Gaussian processes NeurIPS 2011 Bayesian Spike-Triggered Covariance Analysis NeurIPS 2011 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NeurIPS 2009 Characterizing neural dependencies with copula models NeurIPS 2008 Neural characterization in partially observed populations of spiking neurons NeurIPS 2007