Optimization Principles for the Neural Code. - Michael Robert DeWeese (NIPS, 1995)

Asymmetric Dynamics in Optimal Variance Adaptation. - Michael Robert DeWeese; Anthony M. Zador (Neural Comput., 1998)

Binary Coding in Auditory Cortex. - Michael Robert DeWeese; Anthony M. Zador (NIPS, 2002)

Minimum Probability Flow Learning. - Jascha Sohl-Dickstein; Peter Battaglino; Michael Robert DeWeese (ICML, 2011)

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 Codes for Speech Predict Spectrotemporal Receptive Fields in the Inferior Colliculus. - Nicole L. Carlson; Vivienne L. Ming; Michael Robert DeWeese (PLoS Comput. Biol., 2012)

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

Hamiltonian Monte Carlo Without Detailed Balance. - Jascha Sohl-Dickstein; Mayur Mudigonda; Michael Robert DeWeese (ICML, 2014)

Time Resolution Dependence of Information Measures for Spiking Neurons: Atoms, Scaling, and Universality. - Sarah E. Marzen; Michael Robert DeWeese; James P. Crutchfield (CoRR, 2015)

Time resolution dependence of information measures for spiking neurons: scaling and universality. - James P. Crutchfield; Michael Robert DeWeese; Sarah E. Marzen (Frontiers Comput. Neurosci., 2015)

A Device for Human Ultrasonic Echolocation. - Jascha Sohl-Dickstein; Santani Teng; Benjamin M. Gaub; Chris C. Rodgers; Crystal Li; Michael Robert DeWeese; Nicol S. Harper (IEEE Trans. Biomed. Eng., 2015)

Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations. - Badr F. Albanna; Christopher Hillar; Jascha Sohl-Dickstein; Michael Robert DeWeese (Entropy, 2017)

Numerically Recovering the Critical Points of a Deep Linear Autoencoder. - Charles G. Frye; Neha S. Wadia; Michael Robert DeWeese; Kristofer E. Bouchard (CoRR, 2019)

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)

On the Sparse Structure of Natural Sounds and Natural Images: Similarities, Differences, and Implications for Neural Coding. - Eric McVoy Dodds; Michael Robert DeWeese (Frontiers Comput. Neurosci., 2019)

Design of optical neural networks with component imprecisions. - Michael Y.-S. Fang; Sasikanth Manipatruni; Casimir Wierzynski; Amir Khosrowshahi; Michael Robert DeWeese (CoRR, 2020)

A new method for parameter estimation in probabilistic models: Minimum probability flow. - Jascha Sohl-Dickstein; Peter Battaglino; Michael Robert DeWeese (CoRR, 2020)

Heterogeneous Synaptic Weighting Improves Neural Coding in the Presence of Common Noise. - Pratik S. Sachdeva; Jesse A. Livezey; Michael Robert DeWeese (Neural Comput., 2020)

Efficient sensory coding of multidimensional stimuli. - Thomas E. Yerxa; Eric Kee; Michael Robert DeWeese; Emily A. Cooper (PLoS Comput. Biol., 2020)

Neural Tangent Kernel Eigenvalues Accurately Predict Generalization. - James B. Simon; Madeline Dickens; Michael Robert DeWeese (CoRR, 2021)

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses. - Charles G. Frye; James Simon; Neha S. Wadia; Andrew Ligeralde; Michael Robert DeWeese; Kristofer E. Bouchard (Neural Comput., 2021)

Reverse Engineering the Neural Tangent Kernel. - James Benjamin Simon; Sajant Anand; Michael Robert DeWeese (ICML, 2022)

The Eigenlearning Framework: A Conservation Law Perspective on Kernel Ridge Regression and Wide Neural Networks. - James B. Simon; Madeline Dickens; Dhruva Karkada; Michael Robert DeWeese (Trans. Mach. Learn. Res., 2023)

Solvable Dynamics of Self-Supervised Word Embeddings and the Emergence of Analogical Reasoning. - Dhruva Karkada; James B. Simon; Yasaman Bahri; Michael Robert DeWeese (CoRR, 2025)

Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks. - Daniel Kunin; Giovanni Luca Marchetti; Feng Chen; Dhruva Karkada; James B. Simon; Michael Robert DeWeese; Surya Ganguli; Nina Miolane (CoRR, 2025)