5 papers
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…
Latent Generative Solvers for Generalizable Long-Term Physics Simulation
Zituo Chen, Sili Deng
Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PDE families, and stability under…
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…
3-D Representations for Hyperspectral Flame Tomography
Nicolas Tricard, Zituo Chen, Sili Deng
Flame tomography is a compelling approach for extracting large amounts of data from experiments via 3-D thermochemical reconstruction. Recent efforts employing neural-network flame…
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…