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ORCIDGerhard Neumann
- > Home > Persons > Gerhard Neumann
Publications
- 2024
[i67]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards. CoRR abs/2406.08440 (2024)- [i65]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Philipp Becker, Aleksandar Taranovic, Onno Grönheim, Luise Kärger, Gerhard Neumann:
Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations. CoRR abs/2406.14161 (2024) - 2023
- [j47]Jairo Inga
, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Simon Rothfuß, Sean Kille, Philipp Dahlinger, Andreas Lindenmann, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine symbiosis: A multivariate perspective for physically coupled human-machine systems. Int. J. Hum. Comput. Stud. 170: 102926 (2023) - [j42]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. Trans. Mach. Learn. Res. 2023 (2023) - [c105]Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann:
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. ICLR 2023 - [c102]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning for Adaptive Mesh Refinement. NeurIPS 2023 - [i58]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning For Adaptive Mesh Refinement. CoRR abs/2304.00818 (2023) - [i49]Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann:
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization. CoRR abs/2310.20574 (2023) - [i48]Philipp Dahlinger, Niklas Freymuth, Michael Volpp, Tai Hoang, Gerhard Neumann:
Latent Task-Specific Graph Network Simulators. CoRR abs/2311.05256 (2023) - 2022
- [i33]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. CoRR abs/2209.11533 (2022) - 2021
- [i19]Jairo Inga, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Sean Kille, Philipp Dahlinger, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine Symbiosis: A Multivariate Perspective for Physically Coupled Human-machine Systems. CoRR abs/2111.14681 (2021)
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