The Union of Manifolds Hypothesis and its Implications for Deep Generative Modelling. - Bradley C. A. Brown; Anthony L. Caterini; Brendan Leigh Ross; Jesse C. Cresswell; Gabriel Loaiza-Ganem (CoRR, 2022)

Relating Regularization and Generalization through the Intrinsic Dimension of Activations. - Bradley C. A. Brown; Jordan Juravsky; Anthony L. Caterini; Gabriel Loaiza-Ganem (CoRR, 2022)

Verifying the Union of Manifolds Hypothesis for Image Data. - Bradley C. A. Brown; Anthony L. Caterini; Brendan Leigh Ross; Jesse C. Cresswell; Gabriel Loaiza-Ganem (ICLR, 2023)

Language Models Inversely Scale on Piecewise Function Evaluation with Biased Examples. - Bradley C. A. Brown; Jordan Juravsky; Atif Mahmud; Wais Shahbaz; Ryan Ehrlich (Tiny Papers @ ICLR, 2023)

Hydragen: High-Throughput LLM Inference with Shared Prefixes. - Jordan Juravsky; Bradley C. A. Brown; Ryan Ehrlich; Daniel Y. Fu; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. - Bradley C. A. Brown; Jordan Juravsky; Ryan Ehrlich; Ronald Clark; Quoc V. Le; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

CodeMonkeys: Scaling Test-Time Compute for Software Engineering. - Ryan Ehrlich; Bradley C. A. Brown; Jordan Juravsky; Ronald Clark; Christopher Ré; Azalia Mirhoseini (CoRR, 2025)