Learning Continuous Distributions: Simulations With Field Theoretic Priors. - Ilya Nemenman; William Bialek (NIPS, 2000)

Occam factors and model-independent Bayesian learning of continuous distributions - Ilya Nemenman; William Bialek (CoRR, 2000)

Information theory and learning: a physical approach - Ilya Nemenman (CoRR, 2000)

Entropy and Inference, Revisited. - Ilya Nemenman; F. Shafee; William Bialek (NIPS, 2001)

Predictability, Complexity, and Learning. - William Bialek; Ilya Nemenman; Naftali Tishby (Neural Comput., 2001)

How is sensory information processed? - Ilya Nemenman (CoRR, 2004)

Information theory, multivariate dependence, and genetic network inference - Ilya Nemenman (CoRR, 2004)

Fluctuation-Dissipation Theorem and Models of Learning. - Ilya Nemenman (Neural Comput., 2005)

Genome-Wide Discovery of Modulators of Transcriptional Interactions in Human B Lymphocytes. - Kai Wang 045; Ilya Nemenman; Nilanjana Banerjee; Adam A. Margolin; Andrea Califano (RECOMB, 2006)

ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context. - Adam A. Margolin; Ilya Nemenman; Katia Basso; Chris Wiggins 001; Gustavo Stolovitzky; Riccardo Dalla Favera; Andrea Califano (BMC Bioinform., 2006)

Neural Coding of Natural Stimuli: Information at Sub-Millisecond Resolution. - Ilya Nemenman; Geoffrey D. Lewen; William Bialek; Robert R. de Ruyter van Steveninck (PLoS Comput. Biol., 2008)

Adiabatic coarse-graining and simulations of stochastic biochemical networks. - Nikolai Sinitsyn; Nicolas W. Hengartner; Ilya Nemenman (Proc. Natl. Acad. Sci. USA, 2009)

Coincidences and Estimation of Entropies of Random Variables with Large Cardinalities. - Ilya Nemenman (Entropy, 2011)

Mass Conservation and Inference of Metabolic Networks from High-Throughput Mass Spectrometry Data. - Pradeep Bandaru; Mukesh Bansal; Ilya Nemenman (J. Comput. Biol., 2011)

Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception. - Vadas Gintautas; Michael I. Ham; Benjamin Kunsberg; Shawn Barr; Steven P. Brumby; Craig Rasmussen; John S. George; Ilya Nemenman; Luís M. A. Bettencourt; Garrett T. Kenyon (PLoS Comput. Biol., 2011)

Continuum dynamics model of the primary visual cortex for contour detection. - Vijay Singh; Martin Tchernookov; Rebecca Butterfield; Ilya Nemenman (CoRR, 2013)

Stereotypical Escape Behavior in Caenorhabditis elegans Allows Quantification of Effective Heat Stimulus Level. - Kawai Leung; Aylia Mohammadi; William S. Ryu; Ilya Nemenman (PLoS Comput. Biol., 2016)

Growth of bacteria in 3-d colonies. - Xinxian Shao; Andrew Mugler; Justin Kim; Ha Jun Jeong; Bruce R. Levin; Ilya Nemenman (PLoS Comput. Biol., 2017)

Simple biochemical networks allow accurate sensing of multiple ligands with a single receptor. - Vijay Singh; Ilya Nemenman (PLoS Comput. Biol., 2017)

Thermodynamic Computing. - Tom Conte 001; Erik DeBenedictis; Natesh Ganesh; Todd Hylton; John Paul Strachan; R. Stanley Williams; Alexander A. Alemi; Lee Altenberg; Gavin E. Crooks; James P. Crutchfield; Lídia del Rio; Josh Deutsch; et al. (CoRR, 2019)

Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons. - Audrey J. Sederberg; Ilya Nemenman (PLoS Comput. Biol., 2020)

Inferring phenomenological models of first passage processes. - Catalina Rivera; David Hofmann; Ilya Nemenman (PLoS Comput. Biol., 2021)

Low probability states, data statistics, and entropy estimation. - Damián G. Hernández; Ahmed Roman; Ilya Nemenman (CoRR, 2022)

Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices. - Arish Alreja; Ilya Nemenman; Christopher J. Rozell (PLoS Comput. Biol., 2022)

Intrinsic Motivation in Dynamical Control Systems. - Stas Tiomkin; Ilya Nemenman; Daniel Polani; Naftali Tishby (CoRR, 2023)

Inferring Local Structure from Pairwise Correlations. - Mahajabin Rahman; Ilya Nemenman (CoRR, 2023)

Bayesian estimation of the Kullback-Leibler divergence for categorical sytems using mixtures of Dirichlet priors. - Francesco Camaglia; Ilya Nemenman; Thierry Mora; Aleksandra M. Walczak (CoRR, 2023)

Deep Variational Multivariate Information Bottleneck - A Framework for Variational Losses. - Eslam Abdelaleem; Ilya Nemenman; K. Michael Martini (CoRR, 2023)

Learning force laws in many-body systems. - Wentao Yu; Eslam Abdelaleem; Ilya Nemenman; Justin C. Burton (CoRR, 2023)

Data Efficiency, Dimensionality Reduction, and the Generalized Symmetric Information Bottleneck. - K. Michael Martini; Ilya Nemenman (Neural Comput., 2024)

Simultaneous Dimensionality Reduction: A Data Efficient Approach for Multimodal Representations Learning. - Eslam Abdelaleem; Ahmed Roman; K. Michael Martini; Ilya Nemenman (Trans. Mach. Learn. Res., 2024)

Accurate Estimation of Mutual Information in High Dimensional Data. - Eslam Abdelaleem; K. Michael Martini; Ilya Nemenman (CoRR, 2025)

Better Together: Cross and Joint Covariances Enhance Signal Detectability in Undersampled Data. - Arabind Swain; Sean Alexander Ridout; Ilya Nemenman (CoRR, 2025)