
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 - 8 of 8
Organ-like three-dimensional cell aggregates developed in the laboratory represent versatile cellular models for drug ...
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 ...
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 ...