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Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations


May 17, 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

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The Impact of Reinitialization on Generalization in Convolutional Neural Networks


Sep 01, 2021
Ibrahim Alabdulmohsin, Hartmut Maennel, Daniel Keysers

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* 12 figures, 7 tables 

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Deep Learning Through the Lens of Example Difficulty


Jun 18, 2021
Robert J. N. Baldock, Hartmut Maennel, Behnam Neyshabur

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* Main paper: 15 pages, 8 figures. Appendix: 31 pages, 40 figures 

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What Do Neural Networks Learn When Trained With Random Labels?


Jun 18, 2020
Hartmut Maennel, Ibrahim Alabdulmohsin, Ilya Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers

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Exact marginal inference in Latent Dirichlet Allocation


Mar 31, 2020
Hartmut Maennel

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Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates


Jun 19, 2019
Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy Mann, Andre Barreto, Sylvain Gelly, Gergely Neu

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Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem


Jul 09, 2018
Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy Mann, Andre Barreto

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Gradient Descent Quantizes ReLU Network Features


Mar 22, 2018
Hartmut Maennel, Olivier Bousquet, Sylvain Gelly

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