Latham, Peter E.

21 publications

ICLRW 2025 A Biologically Plausible Associative Memory Network Mohadeseh Shafiei Kafraj, Dmitry Krotov, Brendan A Bicknell, Peter E. Latham

ICLR 2025 Range, Not Independence, Drives Modularity in Biologically Inspired Representations Will Dorrell, Kyle Hsu, Luke Hollingsworth, Jin Hwa Lee, Jiajun Wu, Chelsea Finn, Peter E. Latham, Timothy Edward John Behrens, James C. R. Whittington

ICML 2025 Training Dynamics of In-Context Learning in Linear Attention Yedi Zhang, Aaditya K Singh, Peter E. Latham, Andrew M Saxe

TMLR 2025 When Are Bias-Free ReLU Networks Effectively Linear Networks? Yedi Zhang, Andrew M Saxe, Peter E. Latham

ICMLW 2024 Modularity in Biologically Inspired Representations Depends on Task Variable Range Independence Will Dorrell, Kyle Hsu, Luke Hollingsworth, Jin Hwa Lee, Jiajun Wu, Chelsea Finn, Peter E. Latham, Timothy Edward John Behrens, James C. R. Whittington

ICML 2024 Understanding Unimodal Bias in Multimodal Deep Linear Networks Yedi Zhang, Peter E. Latham, Andrew M Saxe

ICMLW 2024 When Are Bias-Free ReLU Networks like Linear Networks? Yedi Zhang, Andrew M Saxe, Peter E. Latham

ICLR 2023 Actionable Neural Representations: Grid Cells from Minimal Constraints Will Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington

ICML 2023 Meta-Learning the Inductive Bias of Simple Neural Circuits Will Dorrell, Maria Yuffa, Peter E. Latham

NeurIPS 2022 On the Stability and Scalability of Node Perturbation Learning Naoki Hiratani, Yash Mehta, Timothy Lillicrap, Peter E Latham

NeurIPS 2021 Powerpropagation: A Sparsity Inducing Weight Reparameterisation Jonathan Schwarz, Siddhant Jayakumar, Razvan Pascanu, Peter E Latham, Yee W. Teh

NeurIPS 2021 Towards Biologically Plausible Convolutional Networks Roman Pogodin, Yash Mehta, Timothy Lillicrap, Peter E Latham

NeurIPS 2020 Kernelized Information Bottleneck Leads to Biologically Plausible 3-Factor Hebbian Learning in Deep Networks Roman Pogodin, Peter E. Latham

NeurIPS 2011 How Biased Are Maximum Entropy Models? Jakob H. Macke, Iain Murray, Peter E. Latham

NeurIPS 2007 Neural Characterization in Partially Observed Populations of Spiking Neurons Jonathan W. Pillow, Peter E. Latham

NeCo 2004 Computing and Stability in Cortical Networks Peter E. Latham, Sheila Nirenberg

NeCo 2003 Firing Rate of the Noisy Quadratic Integrate-and-Fire Neuron Nicolas Brunel, Peter E. Latham

NeurIPS 2001 Associative Memory in Realistic Neuronal Networks Peter E. Latham

NeCo 1999 Narrow vs Wide Tuning Curves: What's Best for a Population Code? Alexandre Pouget, Sophie Denève, Jean-Christophe Ducom, Peter E. Latham

NeurIPS 1998 Divisive Normalization, Line Attractor Networks and Ideal Observers Sophie Denève, Alexandre Pouget, Peter E. Latham

NeCo 1998 Statistically Efficient Estimation Using Population Coding Alexandre Pouget, Kechen Zhang, Sophie Denève, Peter E. Latham