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Quantum Machine Learning in Chemical Compound Space.

O Anatole von Lilienfeld
Published in: Angewandte Chemie (International ed. in English) (2018)
Rather than numerically solving the computationally demanding equations of quantum or statistical mechanics, machine learning methods can infer approximate solutions, interpolating previously acquired property data sets of molecules and materials. The case is made for quantum machine learning: An inductive molecular modeling approach which can be applied to quantum chemistry problems.
Keyphrases
  • machine learning
  • molecular dynamics
  • big data
  • artificial intelligence
  • energy transfer
  • monte carlo
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