Peer-reviewed journals and proceedings


  • Kadmon J, Timcheck J and Ganguli S Predictive coding in balanced neural networks with noise, chaos and delays, NeurIPS, 2020

  • Bahri Y, Kadmon J, Pennington J, Schoenholz S, Sohl-Dickstein J and Ganguli, Statistical mechanics of deep learning, Annual Reviews in Condensed Matter, 2020


  • Kadmon J and Ganguli S, Statistical mechanics of low-rank tensor decomposition, J Stat Mech: Theory and Experiments, 2019

  • Marshel, Kim, Machado, Quirin, Kadmon, Benson, Raja, Chibukhchyan, Ramakrishnan, Inoue, Shane, McKnight, Susumu, Kato, Ganguli and Deisseroth, Layer-specific neural ensembles contributing to ignition and plasticity of perception, Science, 2019

  • Wagner MJ, Kim TH, Kadmon J, Nguyen ND, Ganguli S, Schnitzer MJ and Luo L, Cortex-cerebellum dynamics in the execution and learning of a motor task, Cell, 2019


  • Kadmon J and Ganguli S Statistical Mechanics of Low-Rank Tensor Decomposition, NeurIPS, 2018


  • Kadmon J and Sompolinsky H, Optimal architectures in a solvable model of deep networks, NeurIPS, 2016


  • Kadmon J and Sompolinsky, H., Transition to chaos in random neuronal networks. Physical Review X, Physical Review X, 2015

Earlier work

  • Kadmon J, Ishay JS and Bergman DJ, Properties of ultrasonic acoustic resonances for exploitation in comb construction by social hornets and honeybees, Physical Review E, 2009

  • Tsfadia Y, Friedman R, Kadmon J, SelzerA, Nachliel E and Gutman M, Molecular dynamics simulations of palmitate entry into the hydrophobic pocket of the fatty acid binding protein, FEBS letters, 2007

Conference abstracts

  • Timchek J, Kadmon J, Ganguli S, Boahen K, Harnessing noise and disorder to rescue optimal predictive coding, Cosyne 2019

  • Kadmon J and Sompolinsky H, Analytical study of simple deep networks with recursive learning. Cosyne 2018

  • Kadmon J and Sompolinsky H, Sensory processing by deep-networks with layer-localized learning. Cosyne 2017

  • Kadmon J and Sompolinsky H, Optimal architecture in a solvable model for deep networks. Bernstein Conference 2016

  • Kadmon J and Sompolinsky H, Chaos in random neuronal networks of Inhibitory and Excitatory neurons, NCCD 2015

  • Kadmon J and Sompolinsky H. Dynamic mean-field for cortical circuits. ISFN 2014