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Hessische Wissenschaftlerinnen und Wissenschaftler unterschiedlichster Disziplinen benötigen Hochleistungsrechnen für ihre Forschung.
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Displaying 1 - 29 of 29
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 ...
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 ...
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 ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
Deep Implicit Collision Probability Fields
In robotic applications such as autonomous driving and whole-body control, ensuring safety is of utmost importance ...
IngenieurwissenschaftenInformatik
Deep Reinforcement Learning for Robotics
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
IngenieurwissenschaftenInformatik-
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 ...
IngenieurwissenschaftenInformatik 
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 ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik-
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 ...
IngenieurwissenschaftenInformatik 
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 ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
Adaptive Autonomous Assembly
Autonomous robotic assembly requires a well-orchestrated sequence of high-level actions and smooth manipulation ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
Designing an Efficient Neural Architecture Search
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
Measure-Valued Derivatives for Reinforcement Learning
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
IngenieurwissenschaftenInformatik
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 ...
IngenieurwissenschaftenInformatik
Balloon Estimators for Improving and Scaling the Nonparametric Off-Policy Policy Gradient
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...
IngenieurwissenschaftenInformatik-
Constraint Space Projection Reinforcement Learning
The aim of the project is to develop a new family of optimization algorithms to handle convex constraints and evaluate ...
IngenieurwissenschaftenInformatik -
Evaluating and Improving Recurrent Kalman Networks
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
IngenieurwissenschaftenInformatik 
Interpretable Reinforcement Learning
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
Engineering SciencesComputer Science-
Efficient representations of deep neural networks
Deep neural networks (DNNs) have gained extreme popularity in recent years, advancing state-of-the- art results in ...
IngenieurwissenschaftenInformatik
