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ORCIDPhilipp Becker
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2020 – today
- 2024
[j4]Philipp Becker, Sebastian Mossburger, Fabian Otto, Gerhard Neumann:
Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL. RLJ 4: 1619-1655 (2024)- [i21]Fabian Otto, Philipp Becker, Ngo Anh Vien, Gerhard Neumann:
Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation. CoRR abs/2403.04453 (2024) - [i20]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) - [i19]Philipp Becker, Niklas Freymuth, Gerhard Neumann:
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty. CoRR abs/2406.15131 (2024) - [i18]Claudius Kienle, Benjamin Alt, Onur Celik, Philipp Becker, Darko Katic, Rainer Jäkel, Gerhard Neumann:
MuTT: A Multimodal Trajectory Transformer for Robot Skills. CoRR abs/2407.15660 (2024) - [i17]Balázs Gyenes, Nikolai Franke, Philipp Becker, Gerhard Neumann:
PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds. CoRR abs/2410.18800 (2024) - [i16]Emiliyan Gospodinov, Vaisakh Shaj, Philipp Becker, Stefan Geyer, Gerhard Neumann:
Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity. CoRR abs/2411.01342 (2024) - 2023
- [c18]Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann:
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. ICLR 2023 - [c17]Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. ICRA 2023: 2951-2957 - [c16]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. NeurIPS 2023 - [i15]Philipp Becker, Sebastian Markgraf, Fabian Otto, Gerhard Neumann:
Reinforcement Learning from Multiple Sensors via Joint Representations. CoRR abs/2302.05342 (2023) - [i14]Maximilian Xiling Li
, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. CoRR abs/2304.05171 (2023) - [i13]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. CoRR abs/2306.12306 (2023) - [i12]Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann:
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization. CoRR abs/2310.20574 (2023) - 2022
- [j3]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c15]Niklas Freymuth, Nicolas Schreiber, Aleksandar Taranovic, Philipp Becker, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRL 2022: 1379-1389 - [c14]Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. ICLR 2022 - [c13]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. Robotics: Science and Systems 2022 - [i11]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. CoRR abs/2205.13804 (2022) - [i10]Vaisakh Shaj, Dieter Buchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. CoRR abs/2206.14697 (2022) - [i9]Niklas Freymuth, Nicolas Schreiber, Philipp Becker, Aleksandar Taranovic, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRR abs/2210.08121 (2022) - [i8]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. CoRR abs/2210.09256 (2022) - 2021
- [c12]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRL 2021: 1423-1433 - [c11]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Maria Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. ICLR 2021 - [c10]Simon Burton, Iwo Kurzidem, Adrian Schwaiger, Philipp Schleiss, Michael Unterreiner, Torben Gräber, Philipp Becker:
Safety Assurance of Machine Learning for Chassis Control Functions. SAFECOMP 2021: 149-162 - [i7]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. CoRR abs/2101.09207 (2021) - [i6]Niklas Freymuth, Philipp Becker, Gerhard Neumann:
Versatile Inverse Reinforcement Learning via Cumulative Rewards. CoRR abs/2111.07667 (2021) - [i5]Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann:
Switching Recurrent Kalman Networks. CoRR abs/2111.08291 (2021) - [i4]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRR abs/2112.04216 (2021) - 2020
- [c9]Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. CoRL 2020: 765-781 - [c8]Philipp Becker, Oleg Arenz, Gerhard Neumann:
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. ICLR 2020 - [i3]Philipp Becker, Oleg Arenz, Gerhard Neumann:
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. CoRR abs/2001.08682 (2020) - [i2]Vaisakh Shaj, Philipp Becker, Dieter Buchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. CoRR abs/2010.10201 (2020)
2010 – 2019
- 2019
- [c7]Philipp Becker, Harit Pandya, Gregor H. W. Gebhardt, Cheng Zhao, C. James Taylor, Gerhard Neumann:
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces. ICML 2019: 544-552 - [i1]Philipp Becker, Harit Pandya, Gregor H. W. Gebhardt, Cheng Zhao, C. James Taylor, Gerhard Neumann:
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces. CoRR abs/1905.07357 (2019) - 2012
- [j2]Philipp Becker, Julia Nikolaeva:
Das Dilemma der Cloud-Anbieter zwischen US Patriot Act und BDSG. Computer und Recht 28(3): 170-176 (2012) - 2011
- [c6]Philipp Becker, Martin Birtel, Dennis Christmann, Reinhard Gotzhein:
Black-Burst-Based Quality-of-Service Routing (BBQR) for Wireless Ad-Hoc Networks. NOTERE 2011: 1-8 - [c5]Dennis Christmann, Philipp Becker, Reinhard Gotzhein:
Priority Scheduling in SDL. SDL Forum 2011: 202-217 - 2010
- [c4]Philipp Becker, Marc Krämer:
SDL Modules - Concepts and Tool Support. SAM 2010: 1-17
2000 – 2009
- 2009
- [c3]Philipp Becker, Dennis Christmann, Reinhard Gotzhein:
Model-Driven Development of Time-Critical Protocols with SDL-MDD. SDL Forum 2009: 34-52 - 2008
- [j1]Philipp Becker, Reinhard Gotzhein, Thomas Kuhn:
Model-driven Performance Simulation of Self-organizing Systems with PartsSim. Prax. Inf.verarb. Kommun. 31(1): 45-50 (2008) - 2007
- [c2]Philipp Becker, Reinhard Gotzhein, Thomas Kuhn:
MacZ - A Quality-of-Service MAC Layer for Ad-hoc Networks. HIS 2007: 277-282 - 2006
- [c1]Thomas Kuhn, Philipp Becker:
A Simulator Interconnection Framework for the Accurate Performance Simulation of SDL Models. SAM 2006: 133-147
Coauthor Index
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last updated on 2024-12-11 20:42 CET by the dblp team
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