collaborators

5 papers

cs.PF2026

When Structure is Silent: Opportunities for Algorithmic Dispatch in Linear Algebra

Emmanuel Lujan, Alan Edelman

Algorithmic dispatch is essential for performance in linear-algebra-intensive systems. A persistent challenge lies in the treatment of structured matrices. Although such matrices a…

cs.AI2026

Decision-Support and Modeling with Large Language Models for Geothermal Well Arrays

Edwin Ouko, Emmanuel Lujan, Alan Edelman +1

Geothermal well arrays, which organize multiple geothermal wells into carefully planned geometric configurations, provide opportunities to enhance energy production capacity and in…

cs.LG2026

Reinforcement Learning with Verifiable Physics: Post-training LLMs with Continuous Rewards

Pengfei Cai, Utkarsh Utkarsh, Alan Edelman +2

Partial differential equations (PDEs) are foundational to modeling in science and engineering, but constructing reliable numerical solvers remains labor-intensive, demanding expert…

cs.LG2026

SNAP-FM: Sparse Nonlinear Accelerated Projection for Physics-Constrained Generative Modeling

Alaina Kolli, Theodoros Xenakis, Utkarsh Utkarsh +4

Generative models have emerged as scalable surrogates for physical simulation, yet they offer no guarantee that their outputs respect the conservation laws, boundary conditions, an…

cs.LG2025

Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints

Utkarsh Utkarsh, Pengfei Cai, Alan Edelman +2

Deep generative models have recently been applied to physical systems governed by partial differential equations (PDEs), offering scalable simulation and uncertainty-aware inferenc…