Learning Koopman eigenfunctions of stochastic diffusions with optimal importance sampling and ISOKANN

DOI10.1063/5.0140764arXiv2301.00065OpenAlexW4390789263WikidataQ130103850 ScholiaQ130103850MaRDI QIDQ6188560

Enric Ribera Borrell, Marcus Weber, A. Sikorski

Publication date: 7 February 2024

Published in: Journal of Mathematical Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2301.00065

Mathematics Subject Classification ID

Molecular physics (81V55) Computational molecular dynamics in statistical mechanics (82M37)

Cites Work

• The Monte Carlo computation error of transition probabilities
• On the numerical approximation of the Perron-Frobenius and Koopman operator
• Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification
• Importance sampling in path space for diffusion processes with slow-fast variables
• Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
• Metastability in reversible diffusion processes. I: Sharp asymptotics for capacities and exit times
• A Koopman framework for rare event simulation in stochastic differential equations

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