AI RESEARCH
Posterior-First Neural PDE Simulation: Inferring Hidden Problem State from a Single Field
arXiv CS.LG
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ArXi:2605.03247v1 Announce Type: new Neural PDE simulators often receive only a single observed field at deployment. In this setting, a field-to-future predictor can collapse distinct latent problem states into the same deterministic interface, losing the ambiguity needed for reliable rollout and downstream decisions. We propose posterior-first neural PDE simulation: first infer a posterior over the minimal task-sufficient problem state, then condition prediction on that posterior.