AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways
via Contrastive Learning

AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning

2 November 2023

Mohammadamin Tavakoli

Alexander Shmakov

Ann Marie Carlton

David Van Vranken

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Papers citing "AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning"

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Title
Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity Mohammadamin Tavakoli Aaron Mood David Van Vranken Pierre Baldi GNN AI4CE 42 29 0 24 Mar 2021
Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks P. Schwaller Daniel Probst Alain C. Vaucher Vishnu H. Nair D. Kreutter Teodoro Laino J. Reymond 200 232 0 09 Dec 2020
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction P. Schwaller Teodoro Laino John McGuinness A. Horváth Constantine Bekas A. Lee 108 739 0 06 Nov 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,164 0 30 Oct 2017
Retrosynthetic reaction prediction using neural sequence-to-sequence models Bowen Liu Bharath Ramsundar Prasad Kawthekar Jade Shi Joseph Gomes Quang Luu Nguyen Stephen Ho Jack L. Sloane P. Wender Vijay S. Pande 57 418 0 06 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 593 7,455 0 04 Apr 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 171 2,932 0 07 Oct 2016
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 564 27,311 0 01 Sep 2014