conftrace_

Jonathan W Pillow

35 papers · 2007–2024 · 2 conferences · across top CS/AI conferences

Achievements

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+13 more ↓ ๐Ÿงญ Keyword Pioneer ๐ŸŒ‰ Interdisciplinary Bridge ๐ŸŒˆ Renaissance Researcher (6) ๐Ÿ—บ๏ธ Taxonomy Completionist (14) ๐Ÿฃ Hot Topic Early Bird
๐ŸŒ Conference Polyglot (2) ๐Ÿ—บ๏ธ Taxonomy Completionist (14) ๐Ÿงญ Keyword Pioneer ๐ŸŒŸ Keyword Trendsetter Combo (3) ๐Ÿ  Conference Loyalist (34) ๐ŸŒฑ Topic Pioneer ๐Ÿ”ฌ Deep Specialist (15) ๐Ÿ† Keyword Champion (2) ๐Ÿ’Ž Century Club (35) ๐Ÿ“ˆ Trend Setter ๐Ÿ—ƒ๏ธ Keyword Collector (97) โšก Prolific Year (5) ๐Ÿ”ฅ Unstoppable (8)

Conferences

NIPS (34) ICML (1)

Papers

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