
Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Hessian scientists of various disciplines are using High Performance Computers for their research.
Displaying 1 - 22 of 22
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Understanding the underlying reward mechanisms of human locomotion and transferring this knowledge to humanoid robots is ...
Visuotactile sensors are gaining momentum in robotics because they provide high-resolution contact measurements at a ...
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 ...
Autonomous materials discovery with desired properties is one of the ultimate goals for modern materials science, and ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Refractory metal silicide systems like Mo-Si-Ti are expected to be ideal substrates in composite materials for high ...
In wireless communications, beamforming is utilized for the reception and transmission of directional wireless signals ...
Transcription is the process of converting DNA into RNA and is essential to cellular life. The transcription process ...
Deep Learning is the major component of the success of most new Artificial Intelligence applications. A new promising ...
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
Antiferroelectric (AFE) materials have recently been of a great interest, due to their unique applications in the energy ...
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 ...