Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 30 of 39
End-to-end Learning for Multi-Embodiement Locomotion
The rapid development of robotics has enabled legged robots capable of performing highly dynamic tasks such as walking ...
Engineering SciencesComputer Science
Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis
Up-to-date contact-rich manipulation tasks remain one of the grand challenges of robotics. Equipping robots with a sense ...
IngenieurwissenschaftenInformatik-
Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis
Up-to-date contact-rich manipulation tasks remain one of the grand challenges of robotics. Equipping robots with a sense ...
Engineering SciencesComputer Science 
Major-Minor Mean Field Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) remains difficult to scale to many agents. Recent MARL using Mean Field ...
Engineering SciencesComputer Science
Parameter-Efficient Tuning of Pretrained Visual-Language Models in Multitask Robot Learning
General-purpose intelligent robots are expected to simultaneously handle multiple tasks while interpreting various ...
Engineering SciencesComputer Science
SpyFi: Deep Learning for CSI-based Keylogging Side Channel Attacks
During keyboard typing, hand and finger movements induce alterations in Wi-Fi signal propagation, reflected in Channel ...
Engineering SciencesComputer Science-
Amortized Variational Inference by Policy Search
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
Engineering SciencesComputer Science 
CYWARN – Entwicklung von Strategien und Technologien zur Analyse und Kommunikation der Sicherheitslage im Cyberraum II
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Engineering SciencesComputer Science
Deep Implicit Collision Probability Fields
In robotic applications such as autonomous driving and whole-body control, ensuring safety is of utmost importance ...
Engineering SciencesComputer Science
Deep Reinforcement Learning for Robotics
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
Engineering SciencesComputer Science
Detecting Suitcase Damages With Artificial Intelligence – IT-Project Lufthansa
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Engineering SciencesComputer Science-
Gradient-Based Variational Inference by Policy Search
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
Engineering SciencesComputer Science 
Imitation Learning for Lap Time Simulation
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
Engineering SciencesComputer Science-
Impact of Multipath-Effects on Acoustic Keylogging Systems
Acoustic keylogging describes a category of side-channel attacks that recover typed keystrokes from audio-streams of ...
Engineering SciencesComputer Science 
Improving the Understanding of Neuromuscular Gait Control using Deep Reinforcement Learning
Understanding the underlying reward mechanisms of human locomotion and transferring this knowledge to humanoid robots is ...
Engineering SciencesComputer Science
Investigating the Machine Learning-based Cryptanalysis of Lightweight Block Ciphers
Lightweight Cryptography is about developing and analyzing algorithms that provably obtain security goals, such as ...
Engineering SciencesComputer Science
Learning to Plan
Motion planning is a crucial component of autonomous robot systems. It addresses the problem of finding a feasible ...
Engineering SciencesComputer Science
Metric Self-Paced Reinforcement Learning
Reinforcement Learning (RL) is a promising tool for solving complicated control and decision-making tasks in a data ...
Engineering SciencesComputer Science-
Neural Scene Understanding For Robotics
Autonomous robots need to be able to identify and recognize objects in a scene. For this crucial task we need to ...
Engineering SciencesComputer Science 
Policy Optimization with Learning and Planning in Continuous Spaces
Planning algorithms have shown impressive performance in many domains such as chess and Go. In particular, Monte Carlo ...
Engineering SciencesComputer Science
Scalable Task-Driven Robotic Swarm Control via Collision Avoidance and Learning Mean-Field Control
In recent years, reinforcement learning and its multi-agent analogue have achieved great success in solving various ...
Engineering SciencesComputer Science
Active Exploration for Robotic Manipulation
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning ...
Engineering SciencesComputer Science
Adaptive Autonomous Assembly
Autonomous robotic assembly requires a well-orchestrated sequence of high-level actions and smooth manipulation ...
Engineering SciencesComputer Science
Combining Regenerative and Degenerative Methods in Growing Neural Networks
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
Engineering SciencesComputer Science
CYWARN – Entwicklung von Strategien und Technologien zur Analyse und Kommunikation der Sicherheitslage im Cyberraum
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Engineering SciencesComputer Science
Designing an Efficient Neural Architecture Search
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
Engineering SciencesComputer Science
Learning Physically Interactive Behaviours for Human-Robot Interaction
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human’s actions ...
Engineering SciencesComputer Science
Measure-Valued Derivatives for Reinforcement Learning
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
Engineering SciencesComputer Science-
Noise Resilient Empirical Performance Modeling with Deep Neural Networks
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Engineering SciencesComputer Science 
When to Trust Your Model in Model-based Value Expansion?
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
Engineering SciencesComputer Science
