Ari S. Benjamin

According to our database, Ari S. Benjamin authored at least 12 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Walking the Weight Manifold: a Topological Approach to Conditioning Inspired by Neuromodulation.

Ari S. Benjamin, Kyle Daruwalla, Christian Pehle, Anthony M. Zador

CoRR, May, 2025

Token-Level Uncertainty-Aware Objective for Language Model Post-Training.

Tingkai Liu, Ari S. Benjamin, Anthony M. Zador

CoRR, March, 2025

Delays in generalization match delayed changes in representational geometry.

Xingyu Zheng, Kyle Daruwalla, Ari S. Benjamin, David Klindt

Proceedings of UniReps: the Second Edition of the Workshop on Unifying Representations in Neural Models, 2025

2024

Continual learning with the neural tangent ensemble.

Ari S. Benjamin, Christian-Gernot Pehle, Kyle Daruwalla

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

A role for cortical interneurons as adversarial discriminators.

Ari S. Benjamin, Konrad P. Kording

PLoS Comput. Biol., 2023

2022

Interpolating between sampling and variational inference with infinite stochastic mixtures.

Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Object Based Attention Through Internal Gating.

Jordan Lei, Ari S. Benjamin, Konrad P. Kording

CoRR, 2021

Augmenting Supervised Learning by Meta-learning Unsupervised Local Rules.

Jeffrey Cheng, Ari S. Benjamin, Benjamin Lansdell, Konrad Paul Kordin

CoRR, 2021

2020

An adversarial algorithm for variational inference with a new role for acetylcholine.

Ari S. Benjamin, Konrad P. Kording

CoRR, 2020

2019

Measuring and regularizing networks in function space.

Ari S. Benjamin, David Rolnick, Konrad P. Körding

Proceedings of the 7th International Conference on Learning Representations, 2019

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

The Roles of Supervised Machine Learning in Systems Neuroscience.

Joshua I. Glaser, Ari S. Benjamin, Roozbeh Farhoodi, Konrad P. Körding

CoRR, 2018