Analogy between Boltzmann Machines and Feynman Path Integrals-Reference-Cited by-同舟云学术

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Analogy between Boltzmann Machines and Feynman Path Integrals

Published:2023-04-26 Issue:9 Volume:19 Page:2446-2454
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Iyengar Srinivasan S.¹^ORCID,Kais Sabre²^ORCID

Affiliation:

1. Department of Chemistry and Indiana University Quantum Science and Engineering Center (IU-QSEC), Indiana University, Bloomington, Indiana 47405, United States

2. Department of Chemistry, Department of Physics and Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, United States

Funder

Division of Chemistry

Office of Multidisciplinary Activities

Basic Energy Sciences

National Science Foundation

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c00187

Reference56 articles.

1. Improved protein structure prediction using potentials from deep learning

2. Highly accurate protein structure prediction with AlphaFold

3. Quantum machine learning for chemistry and physics

4. Quantum deep learning

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1. Machine Learning the Quantum Mechanical Wave Function;The Journal of Physical Chemistry A;2023-10-31

2. Interpretable Machine Learning of Amino Acid Patterns in Proteins: A Statistical Ensemble Approach;Journal of Chemical Theory and Computation;2023-08-08

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