Articles with public access mandates - Kristof T. SchüttLearn more
Available somewhere: 27
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
Mandates: German Research Foundation, European Commission, Federal Ministry of …
Quantum-chemical insights from deep tensor neural networks
KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko
Nature Communications 8 (13890), 2017
Mandates: US National Science Foundation, German Research Foundation, Federal Ministry …
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
Mandates: German Research Foundation, European Commission, Federal Ministry of …
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
Mandates: US National Science Foundation, German Research Foundation, European …
Machine learning force fields
OT Unke, S Chmiela, HE Sauceda, M Gastegger, I Poltavsky, KT Schütt, ...
Chemical Reviews 121 (16), 10142-10186, 2021
Mandates: Swiss National Science Foundation, German Research Foundation, European …
Equivariant message passing for the prediction of tensorial properties and molecular spectra
KT Schütt, OT Unke, M Gastegger
Proceedings of the 38th International Conference on Machine Learning 139 …, 2021
Mandates: Swiss National Science Foundation, Federal Ministry of Education and …
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
Mandates: German Research Foundation, UK Engineering and Physical Sciences Research …
iNNvestigate neural networks!
M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ...
Journal of machine learning research 20 (93), 1-8, 2019
Mandates: Federal Ministry of Education and Research, Germany
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
Mandates: European Commission, Federal Ministry of Education and Research, Germany
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
Mandates: German Research Foundation, Federal Ministry of Education and Research, Germany
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects
OT Unke, S Chmiela, M Gastegger, KT Schütt, HE Sauceda, KR Müller
Nature communications 12 (1), 7273, 2021
Mandates: Swiss National Science Foundation, German Research Foundation, Federal …
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
Mandates: European Commission, Federal Ministry of Education and Research, Germany
Perspective on integrating machine learning into computational chemistry and materials science
J Westermayr, M Gastegger, KT Schütt, RJ Maurer
The Journal of Chemical Physics 154 (23), 2021
Mandates: Austrian Science Fund, UK Medical Research Council, Federal Ministry of …
Inverse design of 3d molecular structures with conditional generative neural networks
NWA Gebauer, M Gastegger, SSP Hessmann, KR Müller, KT Schütt
Nature communications 13 (1), 973, 2022
Mandates: German Research Foundation, Federal Ministry of Education and Research, Germany
Roadmap on machine learning in electronic structure
HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ...
Electronic Structure 4 (2), 023004, 2022
Mandates: US Department of Energy, Natural Sciences and Engineering Research Council …
Machine learning of solvent effects on molecular spectra and reactions
M Gastegger, KT Schütt, KR Mueller
Chemical Science, 2021
Mandates: German Research Foundation, European Commission, Federal Ministry of …
Autonomous robotic nanofabrication with reinforcement learning
P Leinen, M Esders, KT Schütt, C Wagner, KR Müller, FS Tautz
Science Advances 6 (36), eabb6987, 2020
Mandates: German Research Foundation, European Commission, Federal Ministry of …
A deep neural network for molecular wave functions in quasi-atomic minimal basis representation
M Gastegger, A McSloy, M Luya, KT Schütt, RJ Maurer
The Journal of Chemical Physics 153 (4), 2020
Mandates: UK Engineering and Physical Sciences Research Council, UK Medical Research …
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
Mandates: German Research Foundation
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
KT Schütt, SSP Hessmann, NWA Gebauer, J Lederer, M Gastegger
The Journal of Chemical Physics 158 (14), 2023
Mandates: Federal Ministry of Education and Research, Germany
Publication and funding information is determined automatically by a computer program