Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 24 of 24
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
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
Learning Interpretable Representations for Visuotactile Sensors
Visuotactile sensors are gaining momentum in robotics because they provide high-resolution contact measurements at a ...
Engineering Sciences
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
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
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
Algorithm Unfolding in Multicell Downlink MIMO Precoding
In wireless communications, beamforming is utilized for the reception and transmission of directional wireless signals ...
Engineering SciencesElectrical Engineering and Information Technology
Bayesian Inference of Cyclic Transcription Dynamics
Transcription is the process of converting DNA into RNA and is essential to cellular life. The transcription process ...
Natural SciencesStatistical Physics, Soft Matter, Biological Physics, Nonlinear Dynamics
Deep Reinforcement Learning: Benchmarking, Algorithms and Applications
Deep Learning is the major component of the success of most new Artificial Intelligence applications. A new promising ...
Engineering Sciences
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
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System
Normative computational models of human sensorimotor behavior based on optimal feedback control with signal-dependent ...
Life SciencesNeurosciences
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
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 ...
Engineering SciencesComputer Science-
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 ...
Engineering SciencesComputer Science -
Evaluating and Improving Recurrent Kalman Networks
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
Engineering SciencesComputer Science 
Interpretable Reinforcement Learning
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
Engineering SciencesComputer Science-
Model Learning With Recurrent Kalman Networks
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system ...
Engineering SciencesComputer Science 
Network Traffic Prediction with Neural Networks
The bursty nature of network traffic is one of the main reasons for congestion in data centers, since traffic loads are ...
Engineering SciencesComputer Science-
Performance Modeling at a Discount
Identifying scalability bugs in parallel applications is a vital but also laborious and expensive task. Empirical ...
Engineering SciencesComputer Science -
Stochastic Search for Applications in Robotics
Stochastic-search algorithms are problem independent algorithms well-suited for black-box optimization of an objective ...
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 ...
Engineering SciencesComputer Science
