Metarf: attention-based random forest for reaction yield prediction with a few trails

HIGHLIGHTS

• who: Kexin Chen from the (UNIVERSITY) have published the paper: MetaRF: attention-based random forest for reaction yield prediction with a few trails, in the Journal: (JOURNAL)
• what: The authors focus on the reaction yield prediction problem which assists chemists in selecting high-yield reactions in a new chemical space only with a few experiu2011 mental trials. For instance, in the experiments of_[10, 14, 15], when the testing data do not contain any new reagents that are different from the training set (testing data is randomly selected from the whole dataset, and the rest . . .
  

   

  

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