
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 - 29 of 29
The rapid development of robotics has enabled legged robots capable of performing highly dynamic tasks such as walking ...
The industrial production of high-density polyethylene (HDPE) through the catalytic polymerization of ethene is an ...
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
In the research area of circular building design, design concepts for sustainable masonry are being implemented using ...
Germany has the ambitious goal of covering all electricity generation by renewable sources by 2045. The Kopernikus ...
This work aimed to apply deep learning, specifically Mamba, to the problem of codon optimisation in order to be able to ...
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
A jet engine’s high-pressure turbine, which is located downstream of the combustor, is subject to an extremely high ...
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
Optoelectronic materials have attracted significant attention owing to the global energy shortage and environmental ...
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
Structural engineering, particularly concrete systems, has long focused on understanding the distribution of internal ...
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Earth modeling is a wide field of different scientific domains, e.g., ice-modeling. All domains have in common, that ...
In the context of earth system modeling the simulation of ice-sheets is an important aspect. Ice-sheet modeling contains ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Reinforcement Learning (RL) has proven to be an empirically very successful approach to solving sequential decision ...
Not only in automotive and aviation industries, but also in shipping the engine manufacturer are forced by new ...
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system ...
This project aimed at solving multi-label classification problems using rule learning algorithms. Multi-label ...
The bursty nature of network traffic is one of the main reasons for congestion in data centers, since traffic loads are ...
Identifying scalability bugs in parallel applications is a vital but also laborious and expensive task. Empirical ...
Stochastic-search algorithms are problem independent algorithms well-suited for black-box optimization of an objective ...
Spacecraft missions of the European Space Agency (ESA) are required to meet specific probabilistic requirements ...
Not only in automotive and aviation industries, but also in shipping the engine manufacturer are forced by new ...