4 papers · 1 filter
Learnable composition for neural operators
Zituo Chen, Baiming Zhang, Sili Deng
Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating conditions differ from trai…
Neural operator discovery from heterogeneous trajectories
Zituo Chen, Qiaofeng Li, Jiaxin Hu +1
Neural operators provide data-driven mappings for modeling dynamical systems. Extending them to families of systems typically requires explicit conditioning variables such as physi…
GLU: Global-Local-Uncertainty Fusion for Scalable Spatiotemporal Reconstruction and Forecasting
Linzheng Wang, Jason Chen, Nicolas Tricard +2
Digital twins of complex physical systems are expected to infer unobserved states from sparse measurements and predict their evolution in time, yet these two functions are typicall…
Flow marching for a generative PDE foundation model
Zituo Chen, Sili Deng
Pretraining on large-scale collections of PDE-governed spatiotemporal trajectories has recently shown promise for building generalizable models of dynamical systems. Yet most exist…