| Human-machine symbiosis: A multivariate perspective for physically coupled human-machine systems J Inga, M Ruess, JH Robens, T Nelius, S Rothfuß, S Kille, P Dahlinger, ... International Journal of Human-Computer Studies 170, 102926, 2023 | 31 | 2023 |
| A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models O Arenz, P Dahlinger, Z Ye, M Volpp, G Neumann Transactions on Machine Learning Research, 2023 | 7 | 2023 |
| Swarm reinforcement learning for adaptive mesh refinement N Freymuth, P Dahlinger, T Würth, S Reisch, L Kärger, G Neumann Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| Accurate bayesian meta-learning by accurate task posterior inference M Volpp, P Dahlinger, P Becker, C Daniel, G Neumann The Eleventh International Conference on Learning Representations, 2023 | 2 | 2023 |
| Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations N Freymuth, P Dahlinger, T Würth, P Becker, A Taranovic, O Grönheim, ... arXiv preprint arXiv:2406.14161, 2024 | 1 | 2024 |
| Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards N Freymuth, P Dahlinger, T Würth, S Reisch, L Kärger, G Neumann arXiv preprint arXiv:2406.08440, 2024 | | 2024 |
| Latent Task-Specific Graph Network Simulators P Dahlinger, N Freymuth, M Volpp, T Hoang, G Neumann arXiv preprint arXiv:2311.05256, 2023 | | 2023 |
| Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization P Dahlinger, P Becker, M Hüttenrauch, G Neumann arXiv preprint arXiv:2310.20574, 2023 | | 2023 |
| A First-Order Method for Estimating Natural Gradients for Variational Inference with Gaussians and Gaussian Mixture Models O Arenz, Z Ye, P Dahlinger, G Neumann | | |
Gerhard NeumannProfessor, Karlsruhe Institute of Technology (KIT)Bestätigte E-Mail-Adresse bei robot-learning.de
