Oleg Arenz

According to our database, Oleg Arenz authored at least 28 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Behavior-Constrained Reinforcement Learning with Receding-Horizon Credit Assignment for High-Performance Control.

Siwei Ju, Jan Tauberschmidt, Oleg Arenz, Peter van Vliet, Jan Peters

CoRR, April, 2026

Mathematical Foundations of Modeling ETL Process Chains.

Levin Maier, Lucas Schulze, Robert Lilow, Lukas Hahn, Nikola Krasowski, Arnulf Barth, Sebastian Gaebel, Ferdi Güran, Oliver Hanau, Giovanni Wagner, Falk Borgmann, Oleg Arenz, Jan Peters

CoRR, March, 2026

Boosting deep Reinforcement Learning using pretraining with Logical Options.

Zihan Ye, Phil Chau, Raban Emunds, Jannis Blüml, Cedric Derstroff, Quentin Delfosse, Oleg Arenz, Kristian Kersting

CoRR, March, 2026

GaussTwin: Unified Simulation and Correction with Gaussian Splatting for Robotic Digital Twins.

Yichen Cai, Paul Jansonnie, Cristiana de Farias, Oleg Arenz, Jan Peters

CoRR, March, 2026

2025

Floating-Base Deep Lagrangian Networks.

Lucas Schulze, Juliano Negri, Victor Barasuol, Vivian Suzano Medeiros, Marcelo Becker, Jan Peters, Oleg Arenz

CoRR, October, 2025

Discrete Variational Autoencoding via Policy Search.

Michael Drolet, Firas Al-Hafez, Aditya Bhatt, Jan Peters, Oleg Arenz

CoRR, September, 2025

LODGE: Joint Hierarchical Task Planning and Learning of Domain Models with Grounded Execution.

Claudius Kienle, Benjamin Alt, Oleg Arenz, Jan Peters

CoRR, May, 2025

Learning from Less: Guiding Deep Reinforcement Learning with Differentiable Symbolic Planning.

Zihan Ye, Oleg Arenz, Kristian Kersting

CoRR, May, 2025

Rollout Total Correlation for Deep Reinforcement Learning.

Bang You, Huaping Liu, Jan Peters, Oleg Arenz

Trans. Mach. Learn. Res., 2025

Machine Learning with Physics Knowledge for Prediction: A Survey.

Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An Thai Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles D. Cranmer, Carlo D'Eramo, Fabian Bülow, Tanmay Goyal, Jan Peters, Martin W. Hoffmann

Trans. Mach. Learn. Res., 2025

Context-Aware Deep Lagrangian Networks for Model Predictive Control.

Lucas Schulze, Jan Peters, Oleg Arenz

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

Maximum Total Correlation Reinforcement Learning.

Bang You, Puze Liu, Huaping Liu, Jan Peters, Oleg Arenz

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2023

Digital Twin of a Driver-in-the-Loop Race Car Simulation With Contextual Reinforcement Learning.

Siwei Ju, Peter van Vliet, Oleg Arenz, Jan Peters

IEEE Robotics Autom. Lett., July, 2023

A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models.

Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann

Trans. Mach. Learn. Res., 2023

LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning.

Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Integrating contrastive learning with dynamic models for reinforcement learning from images.

Bang You, Oleg Arenz, Youping Chen, Jan Peters

Neurocomputing, 2022

Self-supervised Sequential Information Bottleneck for Robust Exploration in Deep Reinforcement Learning.

Bang You, Jingming Xie, Youping Chen, Jan Peters, Oleg Arenz

CoRR, 2022

2020

A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping.

Firas Abi-Farraj, Claudio Pacchierotti, Oleg Arenz, Gerhard Neumann, Paolo Robuffo Giordano

IEEE Trans. Haptics, 2020

Probabilistic Approach to Physical Object Disentangling.

Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann

IEEE Robotics Autom. Lett., 2020

Trust-Region Variational Inference with Gaussian Mixture Models.

Oleg Arenz, Mingjun Zhong, Gerhard Neumann

J. Mach. Learn. Res., 2020

Non-Adversarial Imitation Learning and its Connections to Adversarial Methods.

Oleg Arenz, Gerhard Neumann

CoRR, 2020

Assisted teleoperation in changing environments with a mixture of virtual guides.

Marco Ewerton, Oleg Arenz, Jan Peters

Adv. Robotics, 2020

Deep Adversarial Reinforcement Learning for Object Disentangling.

Melvin Laux, Oleg Arenz, Jan Peters, Joni Pajarinen

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Expected Information Maximization: Using the I-Projection for Mixture Density Estimation.

Philipp Becker, Oleg Arenz, Gerhard Neumann

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Learning Trajectory Distributions for Assisted Teleoperation and Path Planning.

Marco Ewerton, Oleg Arenz, Guilherme Maeda, Dorothea Koert, Zlatko Kolev, Masaki Takahashi, Jan Peters

Frontiers Robotics AI, 2019

2018

Efficient Gradient-Free Variational Inference using Policy Search.

Oleg Arenz, Mingjun Zhong, Gerhard Neumann

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

State-Regularized Policy Search for Linearized Dynamical Systems.

Hany Abdulsamad, Oleg Arenz, Jan Peters, Gerhard Neumann

Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017

2016

Optimal control and inverse optimal control by distribution matching.

Oleg Arenz, Hany Abdulsamad, Gerhard Neumann

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016