3 papers
cs.LG2026
Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries
Hang Zhou, Haixu Wu, Haonan Shangguan +4
Deep learning has emerged as a transformative tool for the neural surrogate modeling of partial differential equations (PDEs), known as neural PDE solvers. However, scaling these s…
eess.SP2026
PhySense: Sensor Placement Optimization for Accurate Physics Sensing
Yuezhou Ma, Haixu Wu, Hang Zhou +3
Physics sensing plays a central role in many scientific and engineering domains, which inherently involves two coupled tasks: reconstructing dense physical fields from sparse obser…
cs.LG2025
ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
Haixu Wu, Yuezhou Ma, Hang Zhou +3
Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs), but their optimization usually faces thorny challenges due…