Jonas Köhler

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Noe FrankFU Berlin, GermanyVerified email at fu-berlin.de
Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
Taco CohenPhD Student, University of AmsterdamVerified email at uva.nl
Mario GeigerÉcole polytechnique fédérale de LausanneVerified email at epfl.ch
Hao WuFree university of BerlinVerified email at zedat.fu-berlin.de
Simon OlssonAssistant Professor, Chalmers University of TechnologyVerified email at chalmers.se
Leon KleinFreie Universität BerlinVerified email at fu-berlin.de
Khalid Al-KhatibLeipzig UniversityVerified email at uni-leipzig.de
Henning WachsmuthPaderborn UniversityVerified email at uni-paderborn.de
Matthias HagenMartin-Luther-Universität Halle-WittenbergVerified email at informatik.uni-halle.de
Benno SteinProfessor of Computer Science, Bauhaus-Universität WeimarVerified email at uni-weimar.de
Frederik HarderMax Planck Institute for Intelligent Systems & University of Tübingen & International Max Planck Research School for Intelligent Systems (IMPRS-IS)Verified email at tuebingen.mpg.de
Andreas KrämerPostDoc, Freie Universität BerlinVerified email at fu-berlin.de
Mijung ParkMax Planck Institute for Intelligent Systems

Jonas Köhler

Freie Universität Berlin

Verified email at fu-berlin.de - Homepage

Machine Learning Normalizing Flows Generative Models


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Spherical CNNs TS Cohen, M Geiger, J Köhler, M Welling International Conference on Learning Representations (ICLR), 2018	383	2018
Boltzmann generators-sampling equilibrium states of many-body systems with deep learning F Noé, S Olsson, J Köhler, H Wu Science 365 (6457), 2019	162	2019
Convolutional Networks for Spherical Signals T Cohen, M Geiger, J Köhler, M Welling ICML workshop on Principled Approaches to Deep Learning (PADL), 2017	52	2017
Cross-Domain Mining of Argumentative Text through Distant Supervision K Al-Khatib, H Wachsmuth, M Hagen, J Köhler, B Stein NAACL-HLT, 2016	42	2016
Equivariant flows: sampling configurations for multi-body systems with symmetric energies J Köhler, L Klein, F Noé NeurIPS workshop on Machine Learning and the Physical Sciences, 2019	21	2019
Stochastic Normalizing Flows H Wu, J Köhler, F Noé Advances in Neural Information Processing Systems (NeurIPS), 2020	9	2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities J Köhler, L Klein, F Noé International Conference on Machine Learning (ICML), 2020	8	2020
Training Neural Networks with Property-Preserving Parameter Perturbations A Krämer, J Köhler, F Noé NeurIPS workshop on Machine Learning and the Physical Sciences, 2020		2020
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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