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stat.ML2022
Toward Unlimited Self-Learning MCMC with Parallel Adaptive Annealing
Yuma Ichikawa, Akira Nakagawa, Hiromoto Masayuki +1
Self-learning Monte Carlo (SLMC) methods are recently proposed to accelerate Markov chain Monte Carlo (MCMC) methods using a machine learning model. With latent generative models,…
cond-mat.dis-nn2022★ 8 cited
Statistical-mechanical study of deep Boltzmann machine given weight parameters after training by singular value decomposition
Yuma Ichikawa, Koji Hukushima
Deep learning methods relying on multi-layered networks have been actively studied in a wide range of fields in recent years, and deep Boltzmann machines(DBMs) is one of them. In t…