Projects per year
Abstract
We train a set of Restricted Boltzmann Machines (RBMs) on one- and two-dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations. We validate the training procedure by monitoring several estimators, including measurements of
the log-likelihood, with the corresponding partition functions estimated using annealed importance
sampling. The effects of various choices of hyper-parameters on training the RBM are discussed
in detail, with a generic prescription provided. Finally, we present a closed form expression for
extracting the values of couplings, for every n-point interaction between the visible nodes of an
RBM, in a binary system such as the Ising model. We aim at using this study as the foundation for
further investigations of less well-known systems.
the log-likelihood, with the corresponding partition functions estimated using annealed importance
sampling. The effects of various choices of hyper-parameters on training the RBM are discussed
in detail, with a generic prescription provided. Finally, we present a closed form expression for
extracting the values of couplings, for every n-point interaction between the visible nodes of an
RBM, in a binary system such as the Ising model. We aim at using this study as the foundation for
further investigations of less well-known systems.
| Original language | English |
|---|---|
| Number of pages | 31 |
| Journal | Physical review B |
| DOIs | |
| Publication status | Published - 7 Aug 2019 |
Keywords / Materials (for Non-textual outputs)
- physics.comp-ph
- cond-mat.stat-mech
- hep-lat
Fingerprint
Dive into the research topics of 'Machine learning determination of dynamical parameters: The Ising model case'. Together they form a unique fingerprint.Projects
- 2 Finished
-
Particle Theory at the Higgs Centre
Ball, R. (Principal Investigator), Boyle, P. (Co-investigator), Del Debbio, L. (Co-investigator), Gardi, E. (Co-investigator), Horsley, R. (Co-investigator), Kennedy, A. (Co-investigator), O'Connell, D. (Co-investigator), Smillie, J. (Co-investigator) & Zwicky, R. (Co-investigator)
1/10/17 → 30/09/21
Project: Research
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High-performance computing at the high-energy frontier: results for the LHC
Del Debbio, L. (Principal Investigator)
1/01/15 → 31/12/19
Project: Research
Profiles
-
Ava Khamseh
- MRC Human Genetics Unit
- School of Informatics - Lecturer in Biomedical Artificial Intelligence
- Institute for Adaptive and Neural Computation
- Institute of Genetics and Cancer
Person: Academic: Research Active