705 citations · 843 across the 9 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
Latent-MoE: Domain-Aware Mixture-of-Experts for PDEs with Multi-Regime Physics
Hanwen Wang, Paris Perdikaris
Physics-informed neural networks (PINNs) struggle on PDEs whose governing physics varies across the domain. We trace this to a structural property of standard coordinate networks:…
quant-ph2026
Toward General Quantum Control with Physics-Informed Large Language Models
Yusheng Zhao, Han Wang, Xin Liu +10
Quantum control is essential for quantum information science and technology, yet designing high-fidelity control protocols remains challenging due to complex optimization landscape…
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…