Search Machine Learning Repository:
All publications by Liam Paninski
authors venues years



Clustered factor analysis of multineuronal spike data
Lars Buesing, Timothy A. Machado, John P. Cunningham and Liam Paninski
Advances in Neural Information Processing Systems 27, 2014


A multi-agent control framework for co-adaptation in brain-computer interfaces
Josh S. Merel, Roy Fox, Tony Jebara and Liam Paninski
Advances in Neural Information Processing Systems 26, 2013


Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions
Ari Pakman and Liam Paninski
Advances in Neural Information Processing Systems 26, 2013


Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions
Eftychios A. Pnevmatikakis and Liam Paninski
Advances in Neural Information Processing Systems 26, 2013


Robust learning of low-dimensional dynamics from large neural ensembles
David Pfau, Eftychios A. Pnevmatikakis and Liam Paninski
Advances in Neural Information Processing Systems 26, 2013


Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits
Ben Shababo, Brooks Paige, Ari Pakman and Liam Paninski
Advances in Neural Information Processing Systems 26, 2013


Low rank continuous-space graphical models
Carl Smith, Frank Wood and Liam Paninski
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Fast interior-point inference in high-dimensional sparse, penalized state-space models
Eftychios A. Pnevmatikakis and Liam Paninski
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Information Rates and Optimal Decoding in Large Neural Populations
Kamiar R. Rad and Liam Paninski
Advances in Neural Information Processing Systems 24, 2011


Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds
Jeremy Lewi, Robert Butera, David M. Schneider, Sarah Woolley and Liam Paninski
Advances in Neural Information Processing Systems 21, 2008


Efficient active learning with generalized linear models
Jeremy Lewi, Robert J. Butera and Liam Paninski
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Real-time adaptive information-theoretic optimization of neurophysiology experiments
Jeremy Lewi, Robert Butera and Liam Paninski
Advances in Neural Information Processing Systems 19, 2006


Large-scale biophysical parameter estimation in single neurons via constrained linear regression
Misha Ahrens, Liam Paninski and Quentin J. Huys
Advances in Neural Information Processing Systems 18, 2005


Nonparametric inference of prior probabilities from Bayes-optimal behavior
Liam Paninski
Advances in Neural Information Processing Systems 18, 2005


Variational Minimax Estimation of Discrete Distributions under KL Loss
Liam Paninski
Advances in Neural Information Processing Systems 17, 2004


Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning
Liam Paninski
Advances in Neural Information Processing Systems 17, 2004


Design of Experiments via Information Theory
Liam Paninski
Advances in Neural Information Processing Systems 16, 2003


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


Convergence Properties of Some Spike-Triggered Analysis Techniques
Liam Paninski
Advances in Neural Information Processing Systems 15, 2002