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math.NA2021★ 7 cited
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems
Nikolas Nüsken, Lorenz Richter
Solving high-dimensional partial differential equations is a recurrent challenge in economics, science and engineering. In recent years, a great number of computational approaches…
stat.ML2021
Bayesian Learning via Neural Schrödinger-Föllmer Flows
Francisco Vargas, Andrius Ovsianas, David Fernandes +3
In this work we explore a new framework for approximate Bayesian inference in large datasets based on stochastic control (i.e. Schrödinger bridges). We advocate stochastic control…