How Should Prey Animals Respond to Uncertain Threats? - Joel Zylberberg; Michael Robert DeWeese (Frontiers Comput. Neurosci., 2011)

A Sparse Coding Model with Synaptically Local Plasticity and Spiking Neurons Can Account for the Diverse Shapes of V1 Simple Cell Receptive Fields. - Joel Zylberberg; Jason Timothy Murphy; Michael Robert DeWeese (PLoS Comput. Biol., 2011)

Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images. - Joel Zylberberg; Michael Robert DeWeese (PLoS Comput. Biol., 2013)

The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes. - Yu Hu; Joel Zylberberg; Eric Shea-Brown (PLoS Comput. Biol., 2014)

Triplet correlations among similarly tuned cells impact population coding. - Natasha A. Cayco-Gajic; Joel Zylberberg; Eric Shea-Brown (Frontiers Comput. Neurosci., 2015)

Using deep learning to reveal the neural code for images in primary visual cortex. - William F. Kindel; Elijah D. Christensen; Joel Zylberberg (CoRR, 2017)

Robust information propagation through noisy neural circuits. - Joel Zylberberg; Alexandre Pouget; Peter E. Latham; Eric Shea-Brown (PLoS Comput. Biol., 2017)

A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data. - N. Alex Cayco-Gajic; Joel Zylberberg; Eric Shea-Brown (Entropy, 2018)

A self-organizing short-term dynamical memory network. - Callie Federer; Joel Zylberberg (Neural Networks, 2018)

Training neural networks to have brain-like representations improves object recognition performance. - Callie Federer; Haoyan Xu; Alona Fyshe; Joel Zylberberg (CoRR, 2019)

Improved object recognition using neural networks trained to mimic the brain's statistical properties. - Callie Federer; Haoyan Xu; Alona Fyshe; Joel Zylberberg (Neural Networks, 2020)

Different Spectral Representations in Optimized Artificial Neural Networks and Brains. - Richard C. Gerum; Cassidy Pirlot; Alona Fyshe; Joel Zylberberg (CoRR, 2022)

Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer. - Cassidy Pirlot; Richard C. Gerum; Cory Efird; Joel Zylberberg; Alona Fyshe (CoRR, 2022)

Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models. - Cory Efird; Alex Murphy; Joel Zylberberg; Alona Fyshe (CoRR, 2023)

Correcting Biased Centered Kernel Alignment Measures in Biological and Artificial Neural Networks. - Alex Murphy; Joel Zylberberg; Alona Fyshe (CoRR, 2024)

What's the Opposite of a Face? Finding Shared Decodable Concepts and their Negations in the Brain. - Cory Efird; Alex Murphy; Joel Zylberberg; Alona Fyshe (CoRR, 2024)

Fine Granularity Is Critical for Intelligent Neural Network Pruning. - Alex Heyman; Joel Zylberberg (Neural Comput., 2024)

Finding Shared Decodable Concepts and their Negations in the Brain. - Cory Daniel Efird; Alex Murphy; Joel Zylberberg; Alona Fyshe (ICLR, 2025)

Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring. - Alex Heyman; Joel Zylberberg (CoRR, 2025)

Reasoning Large Language Model Errors Arise from Hallucinating Critical Problem Features. - Alex Heyman; Joel Zylberberg (CoRR, 2025)