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All publications by Jonathan W. Pillow
authors venues years



Convolutional spike-triggered covariance analysis for neural subunit models
Anqi Wu, Il M. Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 28, 2015


Optimal prior-dependent neural population codes under shared input noise
Agnieszka Grabska-barwinska and Jonathan W. Pillow
Advances in Neural Information Processing Systems 27, 2014


Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit
Karin C. Knudson, Jacob Yates, Alexander Huk and Jonathan W. Pillow
Advances in Neural Information Processing Systems 27, 2014


Low-dimensional models of neural population activity in sensory cortical circuits
Evan W. Archer, Urs Koster, Jonathan W. Pillow and Jakob H. Macke
Advances in Neural Information Processing Systems 27, 2014


Inferring synaptic conductances from spike trains with a biophysically inspired point process model
Kenneth W. Latimer, E. J. Chichilnisky, Fred Rieke and Jonathan W. Pillow
Advances in Neural Information Processing Systems 27, 2014


Sparse Bayesian structure learning with dependent relevance determination priors
Anqi Wu, Mijung Park, Oluwasanmi O. Koyejo and Jonathan W. Pillow
Advances in Neural Information Processing Systems 27, 2014


Spike train entropy-rate estimation using hierarchical Dirichlet process priors
Karin C. Knudson and Jonathan W. Pillow
Advances in Neural Information Processing Systems 26, 2013


Universal models for binary spike patterns using centered Dirichlet processes
Il M. Park, Evan W. Archer, Kenneth Latimer and Jonathan W. Pillow
Advances in Neural Information Processing Systems 26, 2013


Spectral methods for neural characterization using generalized quadratic models
Il M. Park, Evan W. Archer, Nicholas Priebe and Jonathan W. Pillow
Advances in Neural Information Processing Systems 26, 2013


Bayesian inference for low rank spatiotemporal neural receptive fields
Mijung Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 26, 2013


Bayesian entropy estimation for binary spike train data using parametric prior knowledge
Evan W. Archer, Il M. Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 26, 2013


Bayesian active learning with localized priors for fast receptive field characterization
Mijung Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 25, 2012


Bayesian estimation of discrete entropy with mixtures of stick-breaking priors
Evan Archer, Il M. Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 25, 2012


Fully Bayesian inference for neural models with negative-binomial spiking
James Scott and Jonathan W. Pillow
Advances in Neural Information Processing Systems 25, 2012


Active learning of neural response functions with Gaussian processes
Mijung Park, Greg Horwitz and Jonathan W. Pillow
Advances in Neural Information Processing Systems 24, 2011


Bayesian Spike-Triggered Covariance Analysis
Il M. Park and Jonathan W. Pillow
Advances in Neural Information Processing Systems 24, 2011


Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models
Jonathan W. Pillow
Advances in Neural Information Processing Systems 22, 2009


Characterizing neural dependencies with copula models
Pietro Berkes, Frank Wood and Jonathan W. Pillow
Advances in Neural Information Processing Systems 21, 2008


Neural characterization in partially observed populations of spiking neurons
Jonathan W. Pillow and Peter E. Latham
Advances in Neural Information Processing Systems 20, 2007


Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
Liam Paninski, Eero P. Simoncelli and Jonathan W. Pillow
Advances in Neural Information Processing Systems 16, 2003