Tag: Neural PDE Solver

ScientificML

Proposes a variational latent Markov operator framework that encodes physical states as latent distributions and evolves them through probabilistic transitions, addressing error accumulation and distribution shift in neural PDE solvers for long-horizon prediction.

CFD/Computational Fluid Dynamics

A comprehensive benchmark dataset for training and evaluating neural PDE solvers, containing six standard tasks on regular grids, structured grids, and irregular geometries, used for unified evaluation in the ICML 2024 paper Transolver.