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The Schrödinger bridge problem (SBP) finds the most likely stochastic evolution between two probability distributions given a prior stochastic evolution. As well as applications in the natural sciences, problems of this kind...

Machine Learning Stochastic control Schrödinger bridges

AbstractIn this work we explore a new framework for approximate Bayesian inference in large datasets based on stochastic control. We advocate stochastic control as a finite time and low variance...

Schrodinger bridge problem Follmer drift Stochastic control Bayesian inference Bayesian deep learning

The Schrödinger bridge problem (SBP) finds the most likely stochastic evolution between two probability distributions given a prior stochastic evolution. As well as applications in the natural sciences, problems of this kind...

Schrödinger bridges Machine Learning Stochastic control

AbstractIn this work we explore a new framework for approximate Bayesian inference in large datasets based on stochastic control. We advocate stochastic control as a finite time and low variance...

OriginalPaper Schrödinger bridge problem Föllmer drift Stochastic control Bayesian inference Bayesian deep learning

The Schrödinger bridge problem (SBP) finds the most likely stochastic evolution between two probability distributions given a prior stochastic evolution. As well as applications in the natural sciences, problems of this kind...

Schrödinger bridges Machine Learning Stochastic control