Stable by Construction: Variational Latent Markov Operators for Long-Horizon PDE Prediction
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.
See LICENSE file Neural PDE SolverVariational MethodMarkov Dynamics