SPA<sup>H</sup>M(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations-Reference-Cited by-同舟云学术

SPA^HM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations

Published:2024-01-16 Issue:3 Volume:20 Page:1108-1117
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Briling Ksenia R.¹^ORCID,Calvino Alonso Yannick¹^ORCID,Fabrizio Alberto¹²^ORCID,Corminboeuf Clemence¹²^ORCID

Affiliation:

1. Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland

2. National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland

Funder

National Center of Competence in Research Materials? Revolution: Computational Design and Discovery of Novel Materials

?cole Polytechnique F?d?rale de Lausanne

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.3c01040

Reference102 articles.

1. Quantum Chemistry Meets Machine Learning

2. Physics-Inspired Structural Representations for Molecules and Materials

3. Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

4. Ab Initio Machine Learning in Chemical Compound Space

5. Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning

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