Importance sampling in path space for diffusion processes with slow-fast variables
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Publication:681519
DOI10.1007/s00440-017-0755-3zbMath1386.60032arXiv1502.07899OpenAlexW2337000559MaRDI QIDQ681519
Marcus Weber, Christof Schütte, Wei Zhang, Carsten Hartmann
Publication date: 12 February 2018
Published in: Probability Theory and Related Fields (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1502.07899
importance samplingrare eventsMonte Carlo methoddiffusion processchange of measureHamilton-Jacobi-Bellmann equation
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Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space ⋮ Learning-based importance sampling via stochastic optimal control for stochastic reaction networks ⋮ Learning Koopman eigenfunctions of stochastic diffusions with optimal importance sampling and ISOKANN ⋮ Strong averaging principle for two-time-scale stochastic McKean-Vlasov equations ⋮ Pathwise Estimates for Effective Dynamics: The Case of Nonlinear Vectorial Reaction Coordinates ⋮ Jarzynski's equality, fluctuation theorems, and variance reduction: mathematical analysis and numerical algorithms
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