
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 - 55 of 55
Since the beginning of the past century people are interested in the mechanisms which produce the sound caused by a drop ...
In recent years studying the field of aeroacoustics has been received special attention from researches for its ...
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 ...
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 ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Aerodynamic sound contributes significantly to the noise emission of high-speed applications such as trains, aircraft ...
Among the major sources of energy supply, pulverized coal combustion (PCC) will remain one most dominant contributors in ...
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 ...
Identifying scalability bugs in parallel applications is a vital but also laborious and expensive task. Empirical ...
The accurate prediction of combustion processes requires to compute the flow, the concentration, and the chemical ...
Since nearly 86% of the world wide energy demand is obtained through combustion, it is necessary to improve related ...
The objective to reduce the emission of the greenhouse gas CO2 has a high priority in today’s energy supply. However, in ...
The separation of CO2 in oxy-coal combustions is facilitated through firing coal in oxygen (O2) enriched recirculated ...
The ExaFSA project aims to combine the two dominant trends in engineering simulations: multiphysics and high-performance ...
The turbulent flow around blunt bodies induces aeroacoustic sources due to the interaction of the fluid with geometrical ...
Deep neural networks (DNNs) have gained extreme popularity in recent years, advancing state-of-the- art results in ...