
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 - 18 of 18
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 ...
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 ...
Enhanced Geothermal Systems (EGS) exploit the Earth's geothermal energy resources, especially in areas with low ...
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
With the increasing use of renewable energy comes an increasing volatility in energy supply due to external factors ...
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
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 ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
To combat climate change effectively, the use of renewable energy must increase. However, the supply of renewable energy ...
Thin films of lead zirconate-titanate (PZT) belong to the most widely used ferroelectric materials. They possess large ...
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system ...
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 ...
So far, the soil physic characterization of the bedding material is included only rudimentarily into the calculation of ...