A Simulator Interconnection Framework for the Accurate Performance Simulation of SDL Models. - Thomas Kuhn 001; Philipp Becker (SAM, 2006)

MacZ - A Quality-of-Service MAC Layer for Ad-hoc Networks. - Philipp Becker; Reinhard Gotzhein; Thomas Kuhn 001 (HIS, 2007)

Model-driven Performance Simulation of Self-organizing Systems with PartsSim. - Philipp Becker; Reinhard Gotzhein; Thomas Kuhn 001 (Prax. Inf.verarb. Kommun., 2008)

Model-Driven Development of Time-Critical Protocols with SDL-MDD. - Philipp Becker; Dennis Christmann; Reinhard Gotzhein (SDL Forum, 2009)

SDL Modules - Concepts and Tool Support. - Philipp Becker; Marc Krämer (SAM, 2010)

Black-Burst-Based Quality-of-Service Routing (BBQR) for Wireless Ad-Hoc Networks. - Philipp Becker; Martin Birtel; Dennis Christmann; Reinhard Gotzhein (NOTERE, 2011)

Priority Scheduling in SDL. - Dennis Christmann; Philipp Becker; Reinhard Gotzhein (SDL Forum, 2011)

Das Dilemma der Cloud-Anbieter zwischen US Patriot Act und BDSG. - Philipp Becker; Julia Nikolaeva (Computer und Recht, 2012)

Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces. - Philipp Becker; Harit Pandya; Gregor H. W. Gebhardt; Cheng Zhao 002; C. James Taylor; Gerhard Neumann (ICML, 2019)

Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. - Vaisakh Shaj; Philipp Becker; Dieter Büchler; Harit Pandya; Niels van Duijkeren; C. James Taylor; Marc Hanheide; Gerhard Neumann (CoRL, 2020)

Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. - Philipp Becker; Oleg Arenz; Gerhard Neumann (ICLR, 2020)

Specializing Versatile Skill Libraries using Local Mixture of Experts. - Onur Celik; Dongzhuoran Zhou; Ge Li; Philipp Becker; Gerhard Neumann (CoRL, 2021)

Differentiable Trust Region Layers for Deep Reinforcement Learning. - Fabian Otto; Philipp Becker; Ngo Anh Vien; Hanna Carolin Maria Ziesche; Gerhard Neumann (ICLR, 2021)

Safety Assurance of Machine Learning for Chassis Control Functions. - Simon Burton 001; Iwo Kurzidem; Adrian Schwaiger; Philipp Schleiss; Michael Unterreiner; Torben Gräber; Philipp Becker (SAFECOMP, 2021)

Versatile Inverse Reinforcement Learning via Cumulative Rewards. - Niklas Freymuth; Philipp Becker; Gerhard Neumann (CoRR, 2021)

Switching Recurrent Kalman Networks. - Giao Nguyen-Quynh; Philipp Becker; Chen Qiu 001; Maja Rudolph; Gerhard Neumann (CoRR, 2021)

Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. - Niklas Freymuth; Nicolas Schreiber; Aleksandar Taranovic; Philipp Becker; Gerhard Neumann (CoRL, 2022)

Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. - Vaisakh Shaj; Dieter Büchler; Rohit Sonker; Philipp Becker; Gerhard Neumann (ICLR, 2022)

End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. - Moritz Reuss; Niels van Duijkeren; Robert Krug 003; Philipp Becker; Vaisakh Shaj; Gerhard Neumann (Robotics: Science and Systems, 2022)

On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. - Philipp Becker; Gerhard Neumann (Trans. Mach. Learn. Res., 2022)

Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. - Michael Volpp; Philipp Dahlinger; Philipp Becker; Christian Daniel; Gerhard Neumann (ICLR, 2023)

Curriculum-Based Imitation of Versatile Skills. - Maximilian Xiling Li; Onur Celik; Philipp Becker; Denis Blessing; Rudolf Lioutikov; Gerhard Neumann (ICRA, 2023)

Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. - Florian Seligmann; Philipp Becker; Michael Volpp; Gerhard Neumann (NeurIPS, 2023)

Reinforcement Learning from Multiple Sensors via Joint Representations. - Philipp Becker; Sebastian Markgraf; Fabian Otto; Gerhard Neumann (CoRR, 2023)

Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization. - Philipp Dahlinger; Philipp Becker; Maximilian Hüttenrauch; Gerhard Neumann (CoRR, 2023)

PointPatchRL - Masked Reconstruction Improves Reinforcement Learning on Point Clouds. - Balázs Gyenes; Nikolai Franke; Philipp Becker; Gerhard Neumann (CoRL, 2024)

MuTT: A Multimodal Trajectory Transformer for Robot Skills. - Claudius Kienle; Benjamin Alt; Onur Celik; Philipp Becker; Darko Katic; Rainer Jäkel; Gerhard Neumann (IROS, 2024)

Combining Reconstruction and Contrastive Methods for Multimodal Representations in RL. - Philipp Becker; Sebastian Mossburger; Fabian Otto; Gerhard Neumann (RLJ, 2024)

Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation. - Fabian Otto; Philipp Becker; Ngo Anh Vien; Gerhard Neumann (CoRR, 2024)

Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations. - Niklas Freymuth; Philipp Dahlinger; Tobias Würth; Philipp Becker; Aleksandar Taranovic; Onno Grönheim; Luise Kärger; Gerhard Neumann (CoRR, 2024)

KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty. - Philipp Becker; Niklas Freymuth; Gerhard Neumann (CoRR, 2024)

Adaptive World Models: Learning Behaviors by Latent Imagination Under Non-Stationarity. - Emiliyan Gospodinov; Vaisakh Shaj; Philipp Becker; Stefan Geyer; Gerhard Neumann (CoRR, 2024)

Geometry-aware RL for Manipulation of Varying Shapes and Deformable Objects. - Tai Hoang; Huy Le; Philipp Becker; Ngo Anh Vien; Gerhard Neumann (ICLR, 2025)

Efficient Off-Policy Learning for High-Dimensional Action Spaces. - Fabian Otto; Philipp Becker; Ngo Anh Vien; Gerhard Neumann (ICLR, 2025)

EDiT: Efficient Diffusion Transformers with Linear Compressed Attention. - Philipp Becker; Abhinav Mehrotra; Ruchika Chavhan; Malcolm Chadwick; Luca Morreale; Mehdi Noroozi; Alberto Gil C. P. Ramos; Sourav Bhattacharya (CoRR, 2025)

AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction. - Niklas Freymuth; Tobias Würth; Nicolas Schreiber; Balázs Gyenes; Andreas Boltres; Johannes Mitsch; Aleksandar Taranovic; Tai Hoang; Philipp Dahlinger; Philipp Becker; Luise Kärger; Gerhard Neumann (CoRR, 2025)