
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 - 30 of 70
Non-covalent interactions (NCIs) not only govern the structure biomacromolecules such as proteins and DNA, but often ...
The computational resources of the Lichtenberg HPC were used in this project to train physics informed machine learning ...
The project seeks to create a comprehensive model linking nanoscale phenomena to larger-scale behaviors to better ...
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
The previous investigation of SnN clusters with N = 6−40 showed that below a clusters size of about 30 atoms, a prolate ...
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
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 ...
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
Vibroacoustic vehicle behavior specifies among others the quality of vehicles and contributes to customer satisfaction ...
In the framework of the Collaborative Research Center (CRC 1487), iron is studied as a substitute for rare-earth metals ...
The project aims to develop a bridging model that connects the nanoscale to the upscaled levels for understanding the ...
Recent work has shown that deep neural networks are able to predict human similarity judgments with high accuracy (e.g ...
Detailed multi-scale modelling provides in-depth insights into the complex phenomena of catalytic systems that typically ...
In the framework of the Collaborative Research Center (CRC 1487), iron is studied as a substitute for rare-earth metals ...
The project focuses on an iron catalysed method to prepare unprecedented chemical synthons, developed in the group of Dr ...
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
This project was a follow-up project for our initial project intended at setting up Lichtenberg Cluster for the use ...
The prediction accuracy of models is affected using deterministic parameters. That is because the uncertainty of these ...
Overall objective of this project is to develop an elementary physical/chemical bridging model for the chemical reaction ...
The previous investigation of neutral SnN clusters with N = 6 - 20 showed that for clusters with N ≤ 15 prolate ...
This project was a follow-up project for our initial project intended at setting up Lichtenberg Cluster for the use ...
Since semiconductors are fundamental for modern technologies, the research is focused on such materials and their ...
The project focuses on an iron catalysed method to prepare unprecedented chemical synthons, developed in the group of Dr ...
In 2018, Gottschall et al. proposed a multi-stimulit concept for magnetocaloric cooling. [1] The energy consumption ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...