Understand
Many important tasks in chemistry revolve around molecules during reactions.
- This requires predictions far from the equilibrium, while most recent work in machine learning for molecules has been focused on equilibrium or near-equilibrium states.
- In this paper we aim to extend this scope in three ways.
- First, we propose the DimeNet++ model, which is 8x faster and 10% more accurate than the original DimeNet on the QM9 benchmark of equilibrium molecules.
Built on
Neural network ensembles
L.K. Hansen and P. Salamon · 1990
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Estimating the mean and variance of the target probability distribution
D.A. Nix and A.S. Weigend · 1994
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Yingkai Zhang and Weitao Yang · 1998
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Quantum chemistry structures and properties of 134 kilo molecules
Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp, and O. Anatole von Lilienfeld · 2014
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A Practicable Real-Space Measure and Visualization of Static Electron-Correlation Effects
Stefan Grimme and Andreas Hansen · 2015
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Machine learning of accurate energy-conserving molecular force fields
Stefan Chmiela, Alexandre Tkatchenko, Huziel E. Sauceda, Igor Poltavsky, Kristof T. Schütt, and Klaus-Robert Müller · 2017
Earlier work this paper cites.
Similar
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Kristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix, Stefan Chmiela, Alexandre Tkatchenko, and Klaus-Robert Müller · 2017
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Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective
Chengqiang Lu, Qi Liu, Chao Wang, Zhenya Huang, Peize Lin, and Lixin He · 2019
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Fast and Accurate Uncertainty Estimation in Chemical Machine Learning
Félix Musil, Michael J. Willatt, Mikhail A. Langovoy, and Michele Ceriotti · 2019
Cited alongside, same era.
Then
Directional Message Passing for Molecular Graphs
Johannes Gasteiger, Janek Groß, and Stephan Günnemann · 2020
Closest in time.
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Lior Hirschfeld, Kyle Swanson, Kevin Yang, Regina Barzilay, and Connor W. Coley · 2020
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QM7-X: A comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
Johannes Hoja, Leonardo Medrano Sandonas, Brian G. Ernst, Alvaro Vazquez-Mayagoitia, Robert A. DiStasio Jr., and Alexandre Tkatchenko · 2020
Closest in time.
Transferable Multi-level Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multi-task Learning
Ziteng Liu, Liqiang Lin, Qingqing Jia, Zheng Cheng, Yanyan Jiang, Yanwen Guo, and Jing Ma · 2020
Closest in time.
OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features
Zhuoran Qiao, Matthew Welborn, Animashree Anandkumar, Frederick R. Manby, and Thomas F. Miller · 2020
Closest in time.
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