11 citations · 26 across the 16 of their papers we have counts for
6 papers · 1 filter
Physical-Field Reconstruction from Sparse Observations: When Are Diffusion Models Preferable to Deterministic Regression?
Hao Zhou, Rui Zhang, Qi Wang +1
Reconstructing physical fields from sparse observations is central to system identification, forecasting, and control, yet sparse measurements generally underdetermine the full fie…
Large language models for partial differential equation workflows
Han Wan, Rui Zhang, Hao Sun
Numerical methods and deep learning have advanced the modelling and simulation of systems governed by partial differential equations (PDEs), while formulating equations, configurin…
Physics Transformer: Tailoring Transformer for General PDE Prediction
Guoze Sun, Rui Zhang, Jiankai Tang +4
Transformer architectures have attracted increasing attention for solving partial differential equations (PDEs), owing to their flexibility in handling irregular discretizations an…
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
Guoze Sun, Tianya Miao, Haoyang Huang +4
Geometry is central to PDE-governed systems, motivating shape optimization and inversion. Classical pipelines conduct costly forward simulation with geometry processing, requiring…
UniFluids: Unified Neural Operator Learning with Conditional Flow-matching
Haosen Li, Qi Meng, Jiahao Li +4
Partial differential equation (PDE) simulation holds extensive significance in scientific research. Currently, the integration of deep neural networks to learn solution operators o…
Optimization and Generation in Aerodynamics Inverse Design
Huaguan Chen, Ning Lin, Luxi Chen +5
Aerodynamic inverse design can improve vehicle and aircraft efficiency, but practical design rarely seeks performance alone: vehicle refinement must reduce drag while preserving vi…