327 citations · 4.5k across the 98 of their papers we have counts for
4 papers · 1 filter
Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit
Wassim Tenachi, Yashar Hezaveh, Laurence Perreault Levasseur +1
Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text --- and tables are arguably the format in which most physical measurement arrives. Did…
Solving Bayesian inverse problems with diffusion priors and off-policy RL
Luca Scimeca, Siddarth Venkatraman, Moksh Jain +14
This paper presents a practical application of Relative Trajectory Balance (RTB), a recently introduced off-policy reinforcement learning (RL) objective that can asymptotically sol…
Improving Gradient-guided Nested Sampling for Posterior Inference
Pablo Lemos, Nikolay Malkin, Will Handley +3
We present a performant, general-purpose gradient-guided nested sampling algorithm, , combining the state of the art in differentiable programming, Hamiltonian slice sa…
On Diffusion Modeling for Anomaly Detection
Victor Livernoche, Vineet Jain, Yashar Hezaveh +1
Known for their impressive performance in generative modeling, diffusion models are attractive candidates for density-based anomaly detection. This paper investigates different var…