Maximilian Karl

Robotics Research (United States) — United States

Computer Science · Physical Sciences

9h-index568citations33works1.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Reinforcement Learning in Robotics(10), Robot Manipulation and Learning(7), Gaussian Processes and Bayesian Inference(5), Muscle activation and electromyography studies(4), Explainable Artificial Intelligence (XAI)(4)

Publications33 total

LIMT: Language-Informed Multi-Task Visual World Models
2025
Accelerating crash simulations with Finite Element Method Integrated Networks (FEMIN): Comparing two approaches to replace large portions of a FEM simulation
Computer Methods in Applied Mechanics and Engineering·2025Open Access
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
arXiv (Cornell University)·2024Open Access
Adapting Deep Variational Bayes Filter for Enhanced Confidence Estimation in Finite Element Method Integrated Networks (FEMIN)
arXiv (Cornell University)·2024Open Access
LIMT: Language-Informed Multi-Task Visual World Models
arXiv (Cornell University)·2024Open Access
Accurate Kinematic Modeling using Autoencoders on Differentiable Joints
2024· 1 cited
Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands
2024
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer
IEEE Robotics and Automation Letters·2024· 10 cited
Overcoming Knowledge Barriers: Online Imitation Learning from Visual Observation with Pretrained World Models
arXiv (Cornell University)·2024Open Access
Editorial: Language, affordance and physics in robot cognition and intelligent systems
Frontiers in Robotics and AI·2024Open Access
Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
2024
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer
arXiv (Cornell University)·2023Open Access
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
arXiv (Cornell University)·2023Open Access
A Strategy for Structuring Teams Collaboration in University Course Projects
2023· 2 citedOpen Access
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces
arXiv (Cornell University)·2022· 1 citedOpen Access
Unsupervised Real-Time Control Through Variational Empowerment
Springer proceedings in advanced robotics·2022· 30 cited
A COMPARATIVE STUDY ON HOW SOCIAL ROBOTS SUPPORT LEARNERS’ MOTIVATION AND LEARNING
ICERI proceedings·2021
Learning to Fly via Deep Model-Based Reinforcement Learning
arXiv (Cornell University)·2020· 24 citedOpen Access
Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations
arXiv (Cornell University)·2019· 1 citedOpen Access
Unsupervised Real-Time Control through Variational Empowerment
arXiv (Cornell University)·2017· 11 citedOpen Access
page 1 of 2Next →

Frequent Co-authors

Patrick van der Smagt(26), Justin Bayer(8), Philip Becker-Ehmck(8), Elie Aljalbout(6), Nutan Chen(5), Maximilian Soelch(4), M. Eder(3), Alois Knoll(3), Stefan Riesner(3), Herke van Hoof(2), Jan Peters(2), Djalel Benbouzid(2), F. Frank(2), Nikolas Wilhelm(2), Sami Haddadin(2), Rainer Burgkart(2), Simon Thel(2), Lars Greve(2), Xingyuan Zhang(2), Marvin Alles(2)