3 papers
cs.LG2026
Small Models, Strong Priors: Architectural Inductive Bias for Parameter-Efficient Neural PDE Solvers
Shyam Sankaran, Hanwen Wang, Paris Perdikaris
Neural PDE solvers have followed the scaling trajectory of vision and language, with recent foundation models reaching billions of parameters. We argue that scale is a poor substit…
cs.LG2025
Simulating Three-dimensional Turbulence with Physics-informed Neural Networks
Sifan Wang, Shyam Sankaran, Xiantao Fan +2
Turbulent fluid flows are among the most computationally demanding problems in science, requiring enormous computational resources that become prohibitive at high flow speeds. Phys…
cs.LG2025
CViT: Continuous Vision Transformer for Operator Learning
Sifan Wang, Jacob H Seidman, Shyam Sankaran +3
Operator learning, which aims to approximate maps between infinite-dimensional function spaces, is an important area in scientific machine learning with applications across various…