3 papers
cs.LG2026
Iterative Refinement Diffusion for Super-Resolved Data Assimilation of Multiscale Physical Systems
Mrigank Dhingra, Ramchandran Muthukumar, Rebecca Willett +1
Recovering high-resolution states from sparse, low-resolution observations is a central challenge in scientific machine learning and data assimilation. Classical data assimilation…
cs.LG2026
Diffusion models recover accurate mixture weights despite score function insensitivity
Andrew Dennehy, Ramchandran Muthukumar, Rebecca Willett +1
Score-based generative models exhibit a puzzling behavior: they often appear to cover all modes of a target multimodal distribution and yet may fail to learn the correct relative m…
cs.CV2025
Disentangling Safe and Unsafe Corruptions via Anisotropy and Locality
Ramchandran Muthukumar, Ambar Pal, Jeremias Sulam +1
State-of-the-art machine learning systems are vulnerable to small perturbations to their input, where ``small'' is defined according to a threat model that assigns a positive threa…