Transferring chemical and energetic knowledge between molecular systems with machine learning

HIGHLIGHTS

  • who: Sajjad Heydari from the University of Exeter, Exeter , QF, UK have published the Article: Transferring chemical and energetic knowledge between molecular systems with machine learning, in the Journal: (JOURNAL) of 24/05/2022
  • what: The authors aimed at the classification of low and high free-energy conformations. The authors demonstrate the ability of the proposed hypergraph neural network (HNN) on a set of transfer learning experiments. The authors show a remarkable classification performance quantified by an Area Under the Curve (AUC) of 0.92. In Fig 4 the authors report a selection of possible . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?