Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
Machine learning algorithms offer new possibilities for automating reaction procedures. The present paper investigates automated reaction’s prediction with Molecular Transformer, the state-of-the-art model for reaction prediction, proposing a new debiased dataset for a realistic assessment of the mo...
Main Authors: | Dávid Péter Kovács, William McCorkindale, Alpha A. Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-03-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-021-21895-w |
Similar Items
-
Political Constitutionalism: A Republican Defence of the Constitutionality of Democracy
by: Chris McCorkindale
Published: (2009-01-01) -
Can you see the writing on my wall? A content analysis of the Fortune 50's Facebook Social Networking Sites
by: Tina McCorkindale
Published: (2010-06-01) -
Reclaiming the public : Hannah Arendt and the political constitution of the United Kingdom
by: McCorkindale, Christopher
Published: (2011) -
The 2-modular representation theory of PSUâ†3(q), q #ident to# 3(mod 4)
by: McCorkindale, Jane
Published: (1990) -
Learning Hierarchical Representations for Explainable Chemical Reaction Prediction
by: Dong, Z., et al.
Published: (2023)