Unifying machine learning and quantum chemistry -- a deep neural network
for molecular wavefunctions

Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions

24 June 2019

Kristof T. Schütt

Papers citing "Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions"

16 / 16 papers shown

Title
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems Yunyang Li Zaishuo Xia Lin Huang Xinran Wei Han Yang ... Zun Wang Chang-Shu Liu Jia Zhang Jia Zhang Mark B. Gerstein 112 2 0 26 Feb 2025
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 78 1,005 0 26 Feb 2019
A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules Lixue Cheng Matthew Welborn Anders S. Christensen Thomas F. Miller 46 93 0 10 Jan 2019
Large Scale GAN Training for High Fidelity Natural Image Synthesis Andrew Brock Jeff Donahue Karen Simonyan 235 5,363 0 28 Sep 2018
Quantum-chemical insights from interpretable atomistic neural networks Kristof T. Schütt M. Gastegger A. Tkatchenko K. Müller AI4CE 63 31 0 27 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 272 895 0 07 Jun 2018
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 78 959 0 22 Feb 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 172 1,828 0 30 Nov 2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions Kristof T. Schütt Pieter-Jan Kindermans Huziel Enoc Sauceda Felix Stefan Chmiela A. Tkatchenko K. Müller 127 1,069 0 26 Jun 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 276 2,254 0 24 Jun 2017
Machine Learning Molecular Dynamics for the Simulation of Infrared Spectra M. Gastegger J. Behler P. Marquetand AI4CE 31 334 0 16 May 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 65 338 0 16 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 350 7,388 0 04 Apr 2017
By-passing the Kohn-Sham equations with machine learning Felix Brockherde Leslie Vogt Li Li M. Tuckerman K. Burke K. Müller AI4CE 58 606 0 09 Sep 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.1K 149,474 0 22 Dec 2014
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M. Rupp A. Tkatchenko K. Müller O. A. von Lilienfeld AI4CE 135 1,581 0 12 Sep 2011