
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 31 - 45 of 45
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 ...
Magnetic materials are key components for energy harvesting and conversion, information technology and sensor ...
The electronic structure plays a key role in determining the physical properties of highly correlated electron systems ...
Normative computational models of human sensorimotor behavior based on optimal feedback control with signal-dependent ...
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human’s actions ...
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 ...
Permanent magnets are an important component in a wide range of everyday devices. Present high performance magnets like ...
Deep neural networks (DNNs) have gained extreme popularity in recent years, advancing state-of-the- art results in ...