Fast and Accurate Modeling of Molecular Atomization Energies with
Machine Learning

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

12 September 2011

O. A. von Lilienfeld

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Papers citing "Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning"

18 / 268 papers shown

Title
Transforming Bell's Inequalities into State Classifiers with Machine Learning Yue-Chi Ma M. Yung 59 77 0 02 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 803 7,519 0 04 Apr 2017
Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders S. J. Wetzel SSL DRL 52 319 0 07 Mar 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 394 1,851 0 02 Mar 2017
Deep learning and the Schrödinger equation Kyle Mills M. Spanner Isaac Tamblyn 84 140 0 05 Feb 2017
Deep Learning for Computational Chemistry Garrett B. Goh Nathan Oken Hodas Abhinav Vishnu AI4CE 102 681 0 17 Jan 2017
Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data Anuj Karpatne G. Atluri James H. Faghmous M. Steinbach A. Banerjee A. Ganguly Shashi Shekhar N. Samatova Vipin Kumar AI4CE 97 1,001 0 27 Dec 2016
Localized Coulomb Descriptors for the Gaussian Approximation Potential James Barker J. Bulin J. Hamaekers Sonja Mathias 31 24 0 16 Nov 2016
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 272 2,962 0 07 Oct 2016
The Many-Body Expansion Combined with Neural Networks Kun Yao John E. Herr John A. Parkhill 86 97 0 22 Sep 2016
By-passing the Kohn-Sham equations with machine learning Felix Brockherde Leslie Vogt Li Li M. Tuckerman K. Burke K. Müller AI4CE 121 607 0 09 Sep 2016
Supervised Learning with Quantum-Inspired Tensor Networks E. Stoudenmire D. Schwab SSL 73 165 0 18 May 2016
Wavelet Scattering Regression of Quantum Chemical Energies M. Hirn S. Mallat N. Poilvert 64 95 0 16 May 2016
Quantum Energy Regression using Scattering Transforms M. Hirn N. Poilvert S. Mallat 74 31 0 06 Feb 2015
Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals Kevin Vu John C. Snyder Li Li M. Rupp Brandon F. Chen Tarek Khelif K. Müller K. Burke 77 100 0 16 Jan 2015
GP-select: Accelerating EM using adaptive subspace preselection Jacquelyn A. Shelton Jan Gasthaus Zhenwen Dai Jörg Lücke Arthur Gretton 97 18 0 10 Dec 2014
Understanding Machine-learned Density Functionals Li Li John C. Snyder I. Pelaschier Jessica Huang U. Niranjan Paul Duncan M. Rupp K. Müller K. Burke 121 152 0 04 Apr 2014
Orbital-free Bond Breaking via Machine Learning John C. Snyder M. Rupp K. Hansen Leo Blooston K. Müller K. Burke 108 115 0 07 Jun 2013