A neural network assisted Metropolis adjusted Langevin algorithm

DOI10.1515/mcma-2020-2060OpenAlexW3029207337MaRDI QIDQ777903

D. Kharzeev

Publication date: 8 July 2020

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mcma-2020-2060

zbMATH Keywords

neural networkMarkov chain Monte Carlo

Mathematics Subject Classification ID

Monte Carlo methods (65C05)

Uses Software

• CVODE
• DAISY

Cites Work

• Approximation and estimation bounds for artificial neural networks
• Optimal scaling for various Metropolis-Hastings algorithms.
• Inference from iterative simulation using multiple sequences
• Markov-chain Monte-Carlo methods and non-identifiabilities
• Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
• Evaluating Derivatives
• Handbook of Markov Chain Monte Carlo
• Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
• Monte Carlo sampling methods using Markov chains and their applications
• Approximation by superpositions of a sigmoidal function
• An adaptive Metropolis algorithm

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