Следене
Jonas Köhler
Jonas Köhler
CuspAI
Потвърден имейл адрес: cusp.ai - Начална страница
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Позовавания
Година
Spherical CNNs
TS Cohen*, M Geiger*, J Köhler*, M Welling
International Conference on Learning Representations (ICLR), 2018
11792018
Boltzmann generators-sampling equilibrium states of many-body systems with deep learning
F Noé*, S Olsson*, J Köhler*, H Wu
Science 365 (6457), 2019
7172019
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
J Köhler*, L Klein*, F Noé
International Conference on Machine Learning (ICML), 2020
2442020
Stochastic Normalizing Flows
H Wu, J Köhler, F Noé
Advances in Neural Information Processing Systems (NeurIPS), 2020
1832020
Equivariant flows: sampling configurations for multi-body systems with symmetric energies
J Köhler, L Klein, F Noé
arXiv preprint arXiv:1910.00753, 2019
802019
Cross-Domain Mining of Argumentative Text through Distant Supervision
K Al-Khatib, H Wachsmuth, M Hagen, J Köhler, B Stein
NAACL-HLT, 2016
762016
Flow-Matching: Efficient Coarse-Graining of Molecular Dynamics without Forces
J Köhler, Y Chen, A Krämer, C Clementi, F Noé
Journal of Chemical Theory and Computation, 2022
612022
Smooth Normalizing Flows
J Köhler*, A Krämer*, F Noé
Advances in Neural Information Processing Systems (NeurIPS), 2021
572021
Generating stable molecules using imitation and reinforcement learning
SA Meldgaard, J Köhler, HL Mortensen, MPV Christiansen, F Noé, ...
Machine Learning: Science and Technology 3 (1), 015008, 2021
222021
Rigid body flows for sampling molecular crystal structures
J Köhler, M Invernizzi, P de Haan, F Noé
International Conference on Machine Learning (ICML), 2023
182023
Training Neural Networks with Property-Preserving Parameter Perturbations
A Krämer, J Köhler, F Noé
NeurIPS workshop on Machine Learning and the Physical Sciences, 2020
3*2020
Highly Accurate Real-space Electron Densities with Neural Networks
L Cheng, PB Szabó, Z Schätzle, DP Kooi, J Köhler, KJH Giesbertz, F Noé, ...
arXiv preprint arXiv:2409.01306, 2024
22024
Machine Learning Driven Simulations of SARS-CoV-2 Fitness Landscape
AEP Durumeric, J Köhler, K Elez, L Raich, PA Suriana, T Sztain
bioRxiv, 2024.09. 20.614179, 2024
2024
Optimal lossy compression for differentially private data release
J Köhler
Informatics Institute, University of Amsterdam, 2018
2018
DP-MAC: The Differentially Private Method of Auxiliary Coordinates for Deep Learning
F Harder, J Köhler, M Welling, M Park
NeurIPS workshop on Privacy Preserving Machine Learning (PPML), 2018
2018
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