Michael Gastegger

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 18

Top Topics

Highly Relevant

Machine Learning

Top Venues

J. Chem. Inf. Model.

Publications

Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
Improved motif-scaffolding with SE(3) flow matching. Trans. Mach. Learn. Res. 2024 (2024)
Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
Improved motif-scaffolding with SE(3) flow matching. CoRR (2024)
Malte Esders, Gimmy Alex Fernandez Ramirez, Michael Gastegger, Satya Swarup Samal
Scaling up machine learning-based chemical plant simulation: A method for fine-tuning a model to induce stable fixed points. Comput. Chem. Eng. 182 (2024)
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
Relevant Walk Search for Explaining Graph Neural Networks. ICML (2023)
Malte Esders, Gimmy Alex Fernandez Ramirez, Michael Gastegger, Satya Swarup Samal
Scaling machine learning-based chemical plant simulation: A method for fine-tuning a model to induce stable fixed points. CoRR (2023)
Daniel Platero-Rochart, Tatyana Krivobokova, Michael Gastegger, Gilbert Reibnegger, Pedro A. Sánchez-Murcia
Prediction of Enzyme Catalysis by Computing Reaction Energy Barriers via Steered QM/MM Molecular Dynamics Simulations and Machine Learning. J. Chem. Inf. Model. 63 (15) (2023)
Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, Oliver T. Unke
Automatic Identification of Chemical Moieties. CoRR (2022)
Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner, Hartmut Maennel, Sergii Kashubin, Daniel Ahlin, Michael Gastegger, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Klaus-Robert Müller
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations. CoRR (2022)
Kristof Schütt, Oliver T. Unke, Michael Gastegger
Equivariant message passing for the prediction of tensorial properties and molecular spectra. ICML (2021)
Oliver T. Unke, Stefan Chmiela, Michael Gastegger, Kristof T. Schütt, Huziel E. Sauceda, Klaus-Robert Müller
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects. CoRR (2021)
Oliver T. Unke, Mihail Bogojeski, Michael Gastegger, Mario Geiger, Tess Smidt, Klaus-Robert Müller
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities. NeurIPS (2021)
Kristof T. Schütt, Oliver T. Unke, Michael Gastegger
Equivariant message passing for the prediction of tensorial properties and molecular spectra. CoRR (2021)
Niklas W. A. Gebauer, Michael Gastegger, Stefaan S. P. Hessmann, Klaus-Robert Müller, Kristof T. Schütt
Inverse design of 3d molecular structures with conditional generative neural networks. CoRR (2021)
Julia Westermayr, Michael Gastegger, Philipp Marquetand
Combining SchNet and SHARC: The SchNarc machine learning approach for excited-state dynamics. CoRR (2020)
Niklas W. A. Gebauer, Michael Gastegger, Kristof Schütt
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules. NeurIPS (2019)
Niklas W. A. Gebauer, Michael Gastegger, Kristof T. Schütt
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules. CoRR (2019)
Kristof T. Schütt, Michael Gastegger, Alexandre Tkatchenko, Klaus-Robert Müller
Quantum-chemical insights from interpretable atomistic neural networks. CoRR (2018)
Niklas W. A. Gebauer, Michael Gastegger, Kristof T. Schütt
Generating equilibrium molecules with deep neural networks. CoRR (2018)