physics-informed-machine-learning
JAX library for neural operator and PDE foundation model training.
Reference datasets for physics parameter estimation and inverse problem benchmarking. Synthetic data with ground truth, experimental trajectories, and paired MCMC posteriors.
Separable operator models for extreme-scale learning of parametric PDEs
