Michael Gastegger
Technische Universität Berlin
H-index: 24
Europe-Germany
Top articles of Michael Gastegger
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments | Science Advances | Oliver T Unke Martin Stöhr Stefan Ganscha Thomas Unterthiner Hartmut Maennel | 2024/4/5 |
Scaling up machine learning-based chemical plant simulation: A method for fine-tuning a model to induce stable fixed points | Computers & Chemical Engineering | Malte Esders Gimmy Alex Fernandez Ramirez Michael Gastegger Satya Swarup Samal | 2024/3/1 |
Improved motif-scaffolding with SE (3) flow matching | arXiv preprint arXiv:2401.04082 | Jason Yim Andrew Campbell Emile Mathieu Andrew YK Foong Michael Gastegger | 2024/1/8 |
Relevant walk search for explaining graph neural networks | ICML | Ping Xiong Thomas Schnake Michael Gastegger Grégoire Montavon Klaus Robert Muller | 2023/4/24 |
SchNetPack 2.0: A neural network toolbox for atomistic machine learning | The Journal of Chemical Physics | Kristof T Schütt Stefaan SP Hessmann Niklas WA Gebauer Jonas Lederer Michael Gastegger | 2023/4/14 |
Automatic identification of chemical moieties | Physical Chemistry Chemical Physics | Jonas Lederer Michael Gastegger Kristof T Schütt Michael Kampffmeyer Klaus-Robert Müller | 2023 |
Fast protein backbone generation with SE (3) flow matching | arXiv preprint arXiv:2310.05297 | Jason Yim Andrew Campbell Andrew YK Foong Michael Gastegger José Jiménez-Luna | 2023/10/8 |
Prediction of enzyme catalysis by computing reaction energy barriers via steered QM/MM Molecular Dynamics Simulations and Machine Learning | Journal of Chemical Information and Modeling | Daniel Platero-Rochart Tatyana Krivobokova Michael Gastegger Gilbert Reibnegger Pedro A Sánchez-Murcia | 2023/7/21 |
Accurate machine learned quantum-mechanical force fields for biomolecular simulations | arXiv preprint arXiv:2205.08306 | Oliver T Unke Martin Stöhr Stefan Ganscha Thomas Unterthiner Hartmut Maennel | 2022/5/17 |
Inverse design of 3d molecular structures with conditional generative neural networks | Nature Communications | Niklas WA Gebauer Michael Gastegger Stefaan SP Hessmann Klaus-Robert Müller Kristof T Schütt | 2022 |
Roadmap on machine learning in electronic structure | Electronic Structure | Heather J Kulik Thomas Hammerschmidt Jonathan Schmidt Silvana Botti Miguel AL Marques | 2022/8/19 |
Deep learning study of tyrosine reveals that roaming can lead to photodamage | Nature Chemistry | Julia Westermayr Michael Gastegger Dóra Vörös Lisa Panzenboeck Florian Joerg | 2022/8 |
Deep integration of machine learning into computational chemistry and materials science | arXiv e-prints | Julia Westermayr Michael Gastegger Kristof T Schütt Reinhard J Maurer | 2021/2 |
Datasets: Machine learning of solvent effects on molecular spectra and reactions | Michael Gastegger Kristof T Schütt Klaus-Robert Müller | 2021/7/26 | |
Machine learning of solvent effects on molecular spectra and reactions | Chemical Science | Michael Gastegger Kristof T Schütt Klaus Robert Mueller | 2021/7/23 |
Combining machine learning and computational chemistry for predictive insights into chemical systems | Chemical Reviews | John A Keith Valentin Vassilev-Galindo Bingqing Cheng Stefan Chmiela Michael Gastegger | 2021/2/12 |
Equivariant message passing for the prediction of tensorial properties and molecular spectra | Kristof T Schütt Oliver T Unke Michael Gastegger | 2021 | |
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects | Nature Communications | Oliver T Unke Stefan Chmiela Michael Gastegger Kristof T Schütt Huziel E Sauceda | 2021/5/1 |
Perspective on integrating machine learning into computational chemistry and materials science | The Journal of Chemical Physics | Julia Westermayr Michael Gastegger Kristof T Schütt Reinhard J Maurer | 2021/6/21 |
SE (3)-equivariant prediction of molecular wavefunctions and electronic densities | Advances in Neural Information Processing Systems (NeurIPS) | Oliver T Unke Mihail Bogojeski Michael Gastegger Mario Geiger Tess Smidt | 2021/6/4 |
Co-Authors
