
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 49
The field of protein engineering is a rapidly evolving area of research that holds great promise for numerous ...
Voltage-dependent K+ channels are facilitators of a diverse set of physiological processes, including neuronal signaling ...
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 ...
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 ...
As facilitators of ionic currents across biological membranes, voltage-dependent K+ channels are involved in a broad ...
The interaction between the Spike (S) glycoprotein and the ACE2 receptor on the host cell constitutes the pivotal ...
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 ...
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 ...
Protein stability in the complex solution environment of the living cell depends on several environmental factors ...
Overall objective of this project is to develop an elementary physical/chemical bridging model for the chemical reaction ...
This project was a follow-up project for our initial project intended at setting up Lichtenberg Cluster for the use ...
The spike glycoprotein's interaction with the ACE2 receptor on the host cell is the crucial initial step for virus entry ...
DNA-PKcs is a gateway protein of the Non-Homologous End Joining DNA Repair Pathway. Which is the process of repairing ...
Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons ...
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 ...