Open-Source Machine Learning in Computational Chemistry-Reference-Cited by-同舟云学术

Open-Source Machine Learning in Computational Chemistry

Published:2023-07-19 Issue:15 Volume:63 Page:4505-4532
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Hagg Alexander¹²^ORCID,Kirschner Karl N.¹³^ORCID

Affiliation:

1. Institute of Technology, Resource and Energy-Efficient Engineering (TREE), University of Applied Sciences Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany

2. Department of Electrical Engineering, Mechanical Engineering and Technical Journalism, University of Applied Sciences Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany

3. Department of Computer Science, University of Applied Sciences Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00643

Reference383 articles.

1. Langenkamp, M.; Yue, D. N. How Open Source Machine Learning Software Shapes AI. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society; ACM: New York, 2022; pp 385–395

2. Open source molecular modeling

3. Deep learning for molecular design—a review of the state of the art

4. Data-Driven Molecular Dynamics: A Multifaceted Challenge

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