4 papers
MNO: Multiscale Neural Operator for 3D Computational Fluid Dynamics
Qinxuan Wang, Chuang Wang, Mingyu Zhang +4
Neural operators have emerged as a powerful data-driven paradigm for solving partial differential equations (PDEs), while their accuracy and scalability are still limited, particul…
Latent Neural Operator Pretraining for Solving Time-Dependent PDEs
Tian Wang, Chuang Wang
Pretraining methods gain increasing attraction recently for solving PDEs with neural operators. It alleviates the data scarcity problem encountered by neural operator learning when…
Training Dynamics of Nonlinear Contrastive Learning Model in the High Dimensional Limit
Lineghuan Meng, Chuang Wang
This letter presents a high-dimensional analysis of the training dynamics for a single-layer nonlinear contrastive learning model. The empirical distribution of the model weights c…
Latent Neural Operator for Solving Forward and Inverse PDE Problems
Tian Wang, Chuang Wang
Neural operators effectively solve PDE problems from data without knowing the explicit equations, which learn the map from the input sequences of observed samples to the predicted…