Maximilian Karl

According to our database, Maximilian Karl authored at least 20 papers between 2013 and 2023.

Collaborative distances:

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

2023

On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer.

Elie Aljalbout, Felix Frank, Maximilian Karl, Patrick van der Smagt

CoRR, 2023

Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models.

Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces.

Elie Aljalbout, Maximilian Karl, Patrick van der Smagt

Proceedings of the Learning for Dynamics and Control Conference, 2023

A Strategy for Structuring Teams Collaboration in University Course Projects.

Chukwuka Victor Obionwu, Maximilian Karl, David Broneske, Anja Hawlitschek, Paul Blockhaus, Gunter Saake

Proceedings of the 20th International Conference on Smart Business Technologies, 2023

2022

Automated feedback on teamwork in programming courses.

Maximilian Karl, Raphael Zender

Proceedings of the DELFI 2022, 2022

2020

Unsupervised Control: Efficient Inference for Time Series Modelling and Intrinsic Motivation.

Maximilian Karl

PhD thesis, 2020

Temperature-Modulated Micromechanical Thermal Analysis with Microstring Resonators Detects Multiple Coherent Features of Small Molecule Glass Transition.

Maximilian Karl, Lasse H. E. Thamdrup, Jukka Rantanen, Anja Boisen, Thomas Rades

Sensors, 2020

Learning to Fly via Deep Model-Based Reinforcement Learning.

Philip Becker-Ehmck, Maximilian Karl, Jan Peters, Patrick van der Smagt

CoRR, 2020

2019

Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations.

Neha Das, Maximilian Karl, Philip Becker-Ehmck, Patrick van der Smagt

CoRR, 2019

Unsupervised Real-Time Control Through Variational Empowerment.

Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt, Justin Bayer

Proceedings of the Robotics Research, 2019

2017

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data.

Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

ML-based tactile sensor calibration: A universal approach.

Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt

CoRR, 2016

Unsupervised preprocessing for Tactile Data.

Maximilian Karl, Justin Bayer, Patrick van der Smagt

CoRR, 2016

Stable reinforcement learning with autoencoders for tactile and visual data.

Herke van Hoof, Nutan Chen, Maximilian Karl, Patrick van der Smagt, Jan Peters

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

Dynamic movement primitives in latent space of time-dependent variational autoencoders.

Nutan Chen, Maximilian Karl, Patrick van der Smagt

Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

2015

Efficient Empowerment.

Maximilian Karl, Justin Bayer, Patrick van der Smagt

CoRR, 2015

Fast Adaptive Weight Noise.

Justin Bayer, Maximilian Karl, Daniela Korhammer, Patrick van der Smagt

CoRR, 2015

2014

Improving approximate RPCA with a k-sparsity prior.

Maximilian Karl, Christian Osendorfer

CoRR, 2014

Continuum worm-like robotic mechanism with decentral control architecture.

Martin Eder, Maximilian Karl, Alois C. Knoll, Stefan Riesner

Proceedings of the 2014 IEEE International Conference on Automation Science and Engineering, 2014

2013

Design of an inherently safe worm-like robot.

Martin Eder, Maximilian Karl, Felix Schultheiss, Johannes Schürmann, Alois C. Knoll, Stefan Riesner

Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics, 2013