3 papers
cs.LG2026
Latent Generative Modeling of Random Fields from Limited Training Data
James E. Warner, Tristan A. Shah, Patrick E. Leser +3
The ability to accurately model random fields plays a critical role in science and engineering for problems involving uncertain, spatially-varying quantities such as heterogeneous…
cond-mat.mtrl-sci2026
Probabilistic calibration of crystal plasticity material models with synthetic global and local data
Joshua D. Pribe, Patrick E. Leser, Saikumar R. Yeratapally +1
Crystal plasticity models connect macroscopic deformation with the physics of microscale slip in polycrystalline materials. These models can be calibrated using global stress-strai…
cs.LG2025
Bayesian Symbolic Regression via Posterior Sampling
Geoffrey F. Bomarito, Patrick E. Leser
Symbolic regression is a powerful tool for discovering governing equations directly from data, but its sensitivity to noise hinders its broader application. This paper introduces a…