
Projekte
Hessische Wissenschaftlerinnen und Wissenschaftler unterschiedlichster Disziplinen benötigen Hochleistungsrechnen für ihre Forschung.
Hessische Wissenschaftlerinnen und Wissenschaftler unterschiedlichster Disziplinen benötigen Hochleistungsrechnen für ihre Forschung.
Displaying 1 - 20 of 20
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
In robotic applications such as autonomous driving and whole-body control, ensuring safety is of utmost importance ...
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
Acoustic keylogging describes a category of side-channel attacks that recover typed keystrokes from audio-streams of ...
Lightweight Cryptography is about developing and analyzing algorithms that provably obtain security goals, such as ...
Reinforcement Learning (RL) is a promising tool for solving complicated control and decision-making tasks in a data ...
Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning ...
Autonomous robotic assembly requires a well-orchestrated sequence of high-level actions and smooth manipulation ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Natural visuomotor control tasks such as pouring liquids into cups are trivial for humans but are challenging to model ...
Transcription is the process of converting DNA into RNA and is essential to cellular life. The transcription process ...
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
Normative computational models of human sensorimotor behavior based on optimal feedback control with signal-dependent ...
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...
The aim of the project is to develop a new family of optimization algorithms to handle convex constraints and evaluate ...
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
Deep neural networks (DNNs) have gained extreme popularity in recent years, advancing state-of-the- art results in ...