Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 7 of 7
Noise Resilient Empirical Performance Modeling with Deep Neural Networks
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
Engineering SciencesComputer Science
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
Reinforcement Learning (RL) has proven to be an empirically very successful approach to solving sequential decision ...
Engineering SciencesComputer Science-
Model Learning With Recurrent Kalman Networks
Recurrent State-space models (RSSMs) are highly expressive models for learning patterns in time series data and system ...
Engineering SciencesComputer Science -
Multi-Label Rule Learning
This project aimed at solving multi-label classification problems using rule learning algorithms. Multi-label ...
Engineering SciencesComputer Science 
Network Traffic Prediction with Neural Networks
The bursty nature of network traffic is one of the main reasons for congestion in data centers, since traffic loads are ...
Engineering SciencesComputer Science-
Performance Modeling at a Discount
Identifying scalability bugs in parallel applications is a vital but also laborious and expensive task. Empirical ...
Engineering SciencesComputer Science -
Stochastic Search for Applications in Robotics
Stochastic-search algorithms are problem independent algorithms well-suited for black-box optimization of an objective ...
Engineering SciencesComputer Science
