The Roles of Supervised Machine Learning in Systems Neuroscience. - Joshua I. Glaser; Ari S. Benjamin; Roozbeh Farhoodi; Konrad P. Körding (CoRR, 2018)

Modern Machine Learning as a Benchmark for Fitting Neural Responses. - Ari S. Benjamin; Hugo L. Fernandes; Tucker Tomlinson; Pavan Ramkumar; Chris VerSteeg; Raeed H. Chowdhury; Lee E. Miller; Konrad P. Körding (Frontiers Comput. Neurosci., 2018)

Measuring and regularizing networks in function space. - Ari S. Benjamin; David Rolnick; Konrad P. Körding (ICLR (Poster), 2019)

An adversarial algorithm for variational inference with a new role for acetylcholine. - Ari S. Benjamin; Konrad P. Kording (CoRR, 2020)

Augmenting Supervised Learning by Meta-learning Unsupervised Local Rules. - Jeffrey Cheng; Ari S. Benjamin; Benjamin Lansdell; Konrad Paul Kordin (CoRR, 2021)

Object Based Attention Through Internal Gating. - Jordan Lei; Ari S. Benjamin; Konrad P. Kording (CoRR, 2021)

Interpolating between sampling and variational inference with infinite stochastic mixtures. - Richard D. Lange; Ari S. Benjamin; Ralf M. Haefner; Xaq Pitkow (UAI, 2022)

A role for cortical interneurons as adversarial discriminators. - Ari S. Benjamin; Konrad P. Kording (PLoS Comput. Biol., 2023)

Continual learning with the neural tangent ensemble. - Ari S. Benjamin; Christian-Gernot Pehle; Kyle Daruwalla (NeurIPS, 2024)

Delays in generalization match delayed changes in representational geometry. - Xingyu Zheng; Kyle Daruwalla; Ari S. Benjamin; David Klindt (UniReps, 2025)

Token-Level Uncertainty-Aware Objective for Language Model Post-Training. - Tingkai Liu; Ari S. Benjamin; Anthony M. Zador (CoRR, 2025)

Walking the Weight Manifold: a Topological Approach to Conditioning Inspired by Neuromodulation. - Ari S. Benjamin; Kyle Daruwalla; Christian Pehle; Anthony M. Zador (CoRR, 2025)