Design of an inherently safe worm-like robot. - Martin Eder; Maximilian Karl; Felix Schultheiss; Johannes Schürmann; Alois C. Knoll; Stefan Riesner (SSRR, 2013)

Continuum worm-like robotic mechanism with decentral control architecture. - Martin Eder; Maximilian Karl; Alois C. Knoll; Stefan Riesner (CASE, 2014)

Improving approximate RPCA with a k-sparsity prior. - Maximilian Karl; Christian Osendorfer (CoRR, 2014)

Fast Adaptive Weight Noise. - Justin Bayer; Maximilian Karl; Daniela Korhammer; Patrick van der Smagt (CoRR, 2015)

Efficient Empowerment. - Maximilian Karl; Justin Bayer; Patrick van der Smagt (CoRR, 2015)

Dynamic movement primitives in latent space of time-dependent variational autoencoders. - Nutan Chen; Maximilian Karl; Patrick van der Smagt (Humanoids, 2016)

Stable reinforcement learning with autoencoders for tactile and visual data. - Herke van Hoof; Nutan Chen; Maximilian Karl; Patrick van der Smagt; Jan Peters 001 (IROS, 2016)

Unsupervised preprocessing for Tactile Data. - Maximilian Karl; Justin Bayer; Patrick van der Smagt (CoRR, 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)

Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. - Maximilian Karl; Maximilian Soelch 001; Justin Bayer; Patrick van der Smagt (ICLR (Poster), 2017)

Unsupervised Real-Time Control Through Variational Empowerment. - Maximilian Karl; Philip Becker-Ehmck; Maximilian Soelch 001; Djalel Benbouzid; Patrick van der Smagt; Justin Bayer (ISRR, 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)

Learning to Fly via Deep Model-Based Reinforcement Learning. - Philip Becker-Ehmck; Maximilian Karl; Jan Peters 001; Patrick van der Smagt (CoRR, 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)

Unsupervised Control: Efficient Inference for Time Series Modelling and Intrinsic Motivation. - Maximilian Karl (2020)

Automated feedback on teamwork in programming courses. - Maximilian Karl; Raphael Zender (DELFI, 2022)

A Strategy for Structuring Teams Collaboration in University Course Projects. - Chukwuka Victor Obionwu; Maximilian Karl; David Broneske; Anja Hawlitschek; Paul Blockhaus; Gunter Saake (ICSBT, 2023)

CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces. - Elie Aljalbout; Maximilian Karl; Patrick van der Smagt (L4DC, 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 (NeurIPS, 2023)

Editorial: Language, affordance and physics in robot cognition and intelligent systems. - Nutan Chen; Walterio W. Mayol-Cuevas; Maximilian Karl; Elie Aljalbout; Andy Zeng 001; Aurelio Cortese; Wolfram Burgard; Herke van Hoof (Frontiers Robotics AI, 2023)

Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands. - Nikolas J. Wilhelm; Claudio Glowalla; Sami Haddadin; Julian Schote; Hannes Höppner; Patrick van der Smagt; Maximilian Karl; Rainer Burgkart (ICRA, 2024)

Accurate Kinematic Modeling using Autoencoders on Differentiable Joints. - Nikolas J. Wilhelm; Sami Haddadin; Rainer Burgkart; Patrick van der Smagt; Maximilian Karl (ICRA, 2024)

Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning. - Marvin Alles; Philip Becker-Ehmck; Patrick van der Smagt; Maximilian Karl (NeurIPS, 2024)

Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models. - Xingyuan Zhang; Philip Becker-Ehmck; Patrick van der Smagt; Maximilian Karl (CoRR, 2024)

LIMT: Language-Informed Multi-Task Visual World Models. - Elie Aljalbout; Nikolaos Sotirakis; Patrick van der Smagt; Maximilian Karl; Nutan Chen (CoRR, 2024)

Adapting Deep Variational Bayes Filter for Enhanced Confidence Estimation in Finite Element Method Integrated Networks (FEMIN). - Simon Thel; Lars Greve; Maximilian Karl; Patrick van der Smagt (CoRR, 2024)

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 (IEEE Robotics Autom. Lett., 2024)

Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models. - Xingyuan Zhang; Philip Becker-Ehmck; Patrick van der Smagt; Maximilian Karl (Trans. Mach. Learn. Res., 2025)