most citedTransient anisotropic kernel for probabilistic learning on manifolds

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stat.ML2026

Physics-informed random neural architectures on compact boundaryless multiply connected manifolds for random-operator models in machine learning and uncertainty quantification

Christian Soize

We introduce stochastic physics-informed neural networks (SPINNs) for stochastic boundary-value problems (SBVPs) with random operators. The method enforces physics through a struct…

stat.ML2024★ 1 cited

Transient anisotropic kernel for probabilistic learning on manifolds

Christian Soize, Roger Ghanem

PLoM (Probabilistic Learning on Manifolds) is a method introduced in 2016 for handling small training datasets by projecting an Itô equation from a stochastic dissipative Hamiltoni…