Kristof T. Schütt

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	Toutes	Depuis 2016
Citations	3135	3098
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indice i10	17	17

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201520162017201820192020202116 23 141 462 801 1427 228

Coauteurs

Klaus-Robert MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Adresse e-mail validée de tu-berlin.de
Alexandre TkatchenkoProfessor of Physics, University of Luxembourg; Visiting Professor, Berlin Big Data CenterAdresse e-mail validée de uni.lu
Pieter-Jan KindermansSenior Research Scientist, Google BrainAdresse e-mail validée de google.com
Michael GasteggerTU BerlinAdresse e-mail validée de tu-berlin.de
Huziel E. SaucedaMachine Learning Group, Technische Universität BerlinAdresse e-mail validée de tu-berlin.de
Maximilian AlberTU BerlinAdresse e-mail validée de tu-berlin.de
Sven DähneAmazonAdresse e-mail validée de amazon.com
Stefan ChmielaTechnische Universität BerlinAdresse e-mail validée de chmiela.com
Igor PoltavskyPostDocAdresse e-mail validée de uni.lu
Dumitru ErhanStaff Research Scientist, Google BrainAdresse e-mail validée de google.com
Been KimGoogle BrainAdresse e-mail validée de csail.mit.edu
Reinhard J. MaurerAssociate Professor, Department of Chemistry, University of WarwickAdresse e-mail validée de warwick.ac.uk
Farhad ArbabzadahBerlin Institute of TechnologyAdresse e-mail validée de tu-berlin.de
Grégoire MontavonTechnische Universität BerlinAdresse e-mail validée de tu-berlin.de
E.K.U. GrossThe Hebrew University of Jerusalem eberhard.gross'at'mail.huji.ac.ilAdresse e-mail validée de mail.huji.ac.il
Antonio SannaMax Plank Institute of microstructure physicsAdresse e-mail validée de mpi-halle.mpg.de
Wojciech SamekHead of AI Department and Explainable AI Group, Fraunhofer HHI, GermanyAdresse e-mail validée de hhi.fraunhofer.de
Philipp SeegererDoctoral Researcher, Machine Learning Group, TU BerlinAdresse e-mail validée de tu-berlin.de
Sebastian Lapuschkin (né Bach)Head of Explainable AI Group, Fraunhofer Heinrich Hertz InstituteAdresse e-mail validée de hhi.fraunhofer.de
Miriam HägeleTechnische Universität BerlinAdresse e-mail validée de tu-berlin.de

Kristof T. Schütt

Technische Universität Berlin

Adresse e-mail validée de tu-berlin.de

machine learning deep learning quantum chemistry


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature Communications 8 (13890), 2017	686	2017
SchNet - a deep learning architecture for molecules and materials KT Schütt, HE Sauceda, PJ Kindermans, A Tkatchenko, KR Müller The Journal of Chemical Physics 148 (24), 241722, 2018	442	2018
Machine Learning of Accurate Energy-Conserving Molecular Force Fields S Chmiela, A Tkatchenko, HE Sauceda, I Poltavsky, KT Schütt, KR Müller Science Advances 3 (5), e1603015, 2017	441	2017
How to represent crystal structures for machine learning: Towards fast prediction of electronic properties KT Schütt, H Glawe, F Brockherde, A Sanna, KR Müller, EKU Gross Phys. Rev. B 89 (20), 205118, 2014	304	2014
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions KT Schütt, PJ Kindermans, HE Sauceda, S Chmiela, A Tkatchenko, ... Advances in Neural Information Processing System 30, 992--1002, 2017	245	2017
Learning how to explain neural networks: PatternNet and PatternAttribution PJ Kindermans, KT Schütt, M Alber, KR Müller, D Erhan, B Kim, S Dähne 6th International Conference on Learning Representations, 2018	229*	2018
The (un) reliability of saliency methods PJ Kindermans, S Hooker, J Adebayo, M Alber, KT Schütt, S Dähne, ... Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 267-280, 2019	217	2019
Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions KT Schütt, M Gastegger, A Tkatchenko, KR Müller, RJ Maurer Nature Communications 10 (1), 1-10, 2019	114	2019
iNNvestigate neural networks! M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ... J. Mach. Learn. Res. 20 (93), 1-8, 2019	111	2019
SchNetPack: A Deep Learning Toolbox For Atomistic Systems KT Schütt, P Kessel, M Gastegger, K Nicoli, A Tkatchenko, KR Müller Journal of chemical theory and computation 15 (1), 448-455, 2019	104	2019
Investigating the influence of noise and distractors on the interpretation of neural networks PJ Kindermans, K Schütt, KR Müller, S Dähne arXiv preprint arXiv:1611.07270, 2016	63	2016
Early Detection of Malicious Behavior in JavaScript Code K Schütt, M Kloft, A Bikadorov, K Rieck Proceedings of the 5th ACM workshop on Security and artificial intelligence …, 2012	30	2012
Capturing intensive and extensive DFT/TDDFT molecular properties with machine learning W Pronobis, KT Schütt, A Tkatchenko, KR Müller The European Physical Journal B 91 (8), 1-6, 2018	29	2018
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules N Gebauer, M Gastegger, KT Schütt Advances in Neural Information Processing Systems, 7566-7578, 2019	23	2019
Machine Learning Meets Quantum Physics KT Schütt, S Chmiela, OA von Lilienfeld, A Tkatchenko, K Tsuda, ... Springer International Publishing, 2020	20	2020
Quantum-chemical insights from interpretable atomistic neural networks KT Schütt, M Gastegger, A Tkatchenko, KR Müller Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 311-330, 2019	15	2019
Generating equilibrium molecules with deep neural networks NWA Gebauer, M Gastegger, KT Schütt NeurIPS Workshop on Machine Learning for Molecules and Materials, 2018	15	2018
Machine learning force fields OT Unke, S Chmiela, HE Sauceda, M Gastegger, I Poltavsky, KT Schütt, ... arXiv preprint arXiv:2010.07067, 2020	8	2020
XAI for graphs: Explaining graph neural network predictions by identifying relevant walks T Schnake, O Eberle, J Lederer, S Nakajima, KT Schütt, KR Müller, ... arXiv preprint arXiv:2006.03589, 2020	8	2020
An Empirical Study on The Properties of Random Bases for Kernel Methods M Alber, PJ Kindermans, KT Schütt, KR Müller, F Sha Advances in Neural Information Processing System 30, 2760--2771, 2017	8	2017

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