Peter E. Latham

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 15

Top Topics

Spiking Neurons

Information Bottleneck

Sparsity Inducing

Top Venues

PLoS Comput. Biol.

J. Comput. Neurosci.

Publications

Yedi Zhang, Andrew Saxe, Peter E. Latham
When Are Bias-Free ReLU Networks Like Linear Networks? CoRR (2024)
Will Dorrell, Peter E. Latham, Tim E. J. Behrens, James C. R. Whittington
Actionable Neural Representations: Grid Cells from Minimal Constraints. ICLR (2023)
Yedi Zhang, Peter E. Latham, Andrew Saxe
A Theory of Unimodal Bias in Multimodal Learning. CoRR (2023)
Will Dorrell, Maria Yuffa, Peter E. Latham
Meta-Learning the Inductive Bias of Simple Neural Circuits. ICML (2023)
Naoki Hiratani, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham
On the Stability and Scalability of Node Perturbation Learning. NeurIPS (2022)
Sina Tootoonian, Andreas T. Schaefer, Peter E. Latham
Sparse connectivity for MAP inference in linear models using sister mitral cells. PLoS Comput. Biol. 18 (1) (2022)
Roman Pogodin, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham
Towards Biologically Plausible Convolutional Networks. CoRR (2021)
Roman Pogodin, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham
Towards Biologically Plausible Convolutional Networks. NeurIPS (2021)
Jonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu, Peter E. Latham, Yee Whye Teh
Powerpropagation: A sparsity inducing weight reparameterisation. NeurIPS (2021)
Jonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu, Peter E. Latham, Yee Whye Teh
Powerpropagation: A sparsity inducing weight reparameterisation. CoRR (2021)
Roman Pogodin, Peter E. Latham
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks. CoRR (2020)
Roman Pogodin, Peter E. Latham
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks. NeurIPS (2020)
Christopher B. Currin, Phumlani N. Khoza, Alexander D. Antrobus, Peter E. Latham, Tim P. Vogels, Joseph V. Raimondo
Think: Theory for Africa. PLoS Comput. Biol. 15 (7) (2019)
Joel Zylberberg, Alexandre Pouget, Peter E. Latham, Eric Shea-Brown
Robust information propagation through noisy neural circuits. PLoS Comput. Biol. 13 (4) (2017)
Laurence Aitchison, Nicola Corradi, Peter E. Latham
Zipf's Law Arises Naturally When There Are Underlying, Unobserved Variables. PLoS Comput. Biol. 12 (12) (2016)
Laurence Aitchison, Dan Bang, Bahador Bahrami, Peter E. Latham
Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making. PLoS Comput. Biol. 11 (10) (2015)
Agnieszka Grabska-Barwinska, Peter E. Latham
How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes? J. Comput. Neurosci. 36 (3) (2014)
Edward Wallace, Hamid Reza Maei, Peter E. Latham
Randomly Connected Networks Have Short Temporal Memory. Neural Comput. 25 (6) (2013)
Agnieszka Grabska-Barwinska, Jeffrey M. Beck, Alexandre Pouget, Peter E. Latham
Demixing odors - fast inference in olfaction. NIPS (2013)
Jakob H. Macke, Iain Murray, Peter E. Latham
Estimation Bias in Maximum Entropy Models. Entropy 15 (8) (2013)
Dan Bang, Riccardo Fusaroli, Kristian Tylén, Karsten Olsen, Peter E. Latham, Jennifer Lau, Andreas Roepstorff, Geraint Rees, Chris D. Frith, Bahador Bahrami
Does interaction matter? Testing whether fast and frugal heuristics can replace interaction in collective decision-making. CogSci (2013)
Jakob H. Macke, Iain Murray, Peter E. Latham
How biased are maximum entropy models? NIPS (2011)
Yasser Roudi, Sheila Nirenberg, Peter E. Latham
Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't. PLoS Comput. Biol. 5 (5) (2009)
Peter E. Latham, Yasser Roudi
Mutual information. Scholarpedia 4 (1) (2009)
Jonathan W. Pillow, Peter E. Latham
Neural characterization in partially observed populations of spiking neurons. NIPS (2007)
Yasser Roudi, Peter E. Latham
A Balanced Memory Network. PLoS Comput. Biol. 3 (9) (2007)
Peter E. Latham, Sheila Nirenberg
Computing and Stability in Cortical Networks. Neural Comput. 16 (7) (2004)
Nicolas Brunel, Peter E. Latham
Firing Rate of the Noisy Quadratic Integrate-and-Fire Neuron. Neural Comput. 15 (10) (2003)
Peter E. Latham
Associative memory in realistic neuronal networks. NIPS (2001)
Alexandre Pouget, Sophie Denève, Jean-Christophe Ducom, Peter E. Latham
Narrow vs Wide Tuning Curves: What's Best for a Population Code? Neural Comput. 11 (1) (1999)
Alexandre Pouget, Kechen Zhang, Sophie Denève, Peter E. Latham
Statistically Efficient Estimation Using Population Coding. Neural Comput. 10 (2) (1998)
Sophie Denève, Alexandre Pouget, Peter E. Latham
Divisive Normalization, Line Attractor Networks and Ideal Observers. NIPS (1998)