标题
The many-body expansion combined with neural networks
作者
关键词
-
出版物
JOURNAL OF CHEMICAL PHYSICS
Volume 146, Issue 1, Pages 014106
出版商
AIP Publishing
发表日期
2017-01-05
DOI
10.1063/1.4973380
参考文献
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- (2016) Michael Gastegger et al. JOURNAL OF CHEMICAL PHYSICS
- Understanding the many-body expansion for large systems. II. Accuracy considerations
- (2016) Ka Un Lao et al. JOURNAL OF CHEMICAL PHYSICS
- Communication: Fitting potential energy surfaces with fundamental invariant neural network
- (2016) Kejie Shao et al. JOURNAL OF CHEMICAL PHYSICS
- Computationally efficient characterization of potential energy surfaces based on fingerprint distances
- (2016) Bastian Schaefer et al. JOURNAL OF CHEMICAL PHYSICS
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- (2016) Li Zhu et al. JOURNAL OF CHEMICAL PHYSICS
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- (2016) Jie Liu et al. Journal of Chemical Theory and Computation
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- (2016) Kun Yao et al. Journal of Chemical Theory and Computation
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- (2016) Jérôme Cuny et al. Journal of Chemical Theory and Computation
- Accurate Composite and Fragment-Based Quantum Chemical Models for Large Molecules
- (2015) Krishnan Raghavachari et al. CHEMICAL REVIEWS
- Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties
- (2015) O. Anatole von Lilienfeld et al. INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
- Machine learning for quantum mechanics in a nutshell
- (2015) Matthias Rupp INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
- Crystal structure representations for machine learning models of formation energies
- (2015) Felix Faber et al. INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
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- (2015) Jun Li et al. JOURNAL OF CHEMICAL PHYSICS
- A permutationally invariant full-dimensional ab initio potential energy surface for the abstraction and exchange channels of the H + CH4 system
- (2015) Jun Li et al. JOURNAL OF CHEMICAL PHYSICS
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- (2015) Gregory R. Medders et al. JOURNAL OF CHEMICAL PHYSICS
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- (2015) K. V. Jovan Jose et al. Journal of Chemical Theory and Computation
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- (2015) Riccardo Conte et al. Journal of Chemical Theory and Computation
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- (2015) Xianfeng Ma et al. Journal of Physical Chemistry Letters
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- (2015) Katja Hansen et al. Journal of Physical Chemistry Letters
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- (2015) S. Alireza Ghasemi et al. PHYSICAL REVIEW B
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- (2014) Ryan M. Richard et al. ACCOUNTS OF CHEMICAL RESEARCH
- Global Potential Energy Surface for the H+CH4↔H2+CH3 Reaction using Neural Networks
- (2014) Xin Xu et al. CHINESE JOURNAL OF CHEMICAL PHYSICS
- Neural network-based approaches for building high dimensional and quantum dynamics-friendly potential energy surfaces
- (2014) Sergei Manzhos et al. INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY
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- (2014) Madan Lamichhane et al. JOURNAL OF CHEMICAL PHYSICS
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- (2014) Madan Lamichhane et al. JOURNAL OF CHEMICAL PHYSICS
- Communication: Separable potential energy surfaces from multiplicative artificial neural networks
- (2014) Werner Koch et al. JOURNAL OF CHEMICAL PHYSICS
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- (2014) Ryan M. Richard et al. JOURNAL OF CHEMICAL PHYSICS
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- (2014) Zhaojun Zhang et al. JOURNAL OF CHEMICAL PHYSICS
- Trouble with the Many-Body Expansion
- (2014) John F. Ouyang et al. Journal of Chemical Theory and Computation
- Advances in molecular quantum chemistry contained in the Q-Chem 4 program package
- (2014) Yihan Shao et al. MOLECULAR PHYSICS
- Modeling electronic quantum transport with machine learning
- (2014) Alejandro Lopez-Bezanilla et al. PHYSICAL REVIEW B
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- (2013) Grégoire Montavon et al. NEW JOURNAL OF PHYSICS
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- (2013) Albert P. Bartók et al. PHYSICAL REVIEW B
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- (2010) Chris M. Handley et al. JOURNAL OF PHYSICAL CHEMISTRY A
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- (2008) Volkan Ediz et al. JOURNAL OF PHYSICAL CHEMISTRY A
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