• Media type: E-Article
  • Title: Lifelong Machine Learning Potentials
  • Contributor: Eckhoff, Marco; Reiher, Markus
  • Published: American Chemical Society (ACS), 2023
  • Published in: Journal of Chemical Theory and Computation, 19 (2023) 12, Seite 3509-3525
  • Language: English
  • DOI: 10.1021/acs.jctc.3c00279
  • ISSN: 1549-9618; 1549-9626
  • Keywords: Physical and Theoretical Chemistry ; Computer Science Applications
  • Origination:
  • University thesis:
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