701 citations · 776 across the 8 of their papers we have counts for
6 papers · 1 filter
PI-MFM: Physics-informed multimodal foundation model for solving partial differential equations
Min Zhu, Jingmin Sun, Zecheng Zhang +2
Partial differential equations (PDEs) govern a wide range of physical systems, and recent multimodal foundation models have shown promise for learning PDE solution operators across…
RED-DiffEq: Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversion
Siming Shan, Min Zhu, Youzuo Lin +1
Partial differential equation (PDE)-governed inverse problems are fundamental across various scientific and engineering applications; yet they face significant challenges due to no…
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
Zhikai Wu, Sifan Wang, Shiyang Zhang +5
Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynam…
Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration
Jonathan E. Lee, Min Zhu, Ziqiao Xi +3
Geological carbon sequestration (GCS) involves injecting CO into subsurface geological formations for permanent storage. Numerical simulations could guide decisions in GCS proj…
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration
Zhongyi Jiang, Min Zhu, Lu Lu
Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliabilit…
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics
Xin-Yang Liu, Min Zhu, Lu Lu +2
Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed…