Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
Kategorie
Jahr
Software
Universität
Cluster
Projekte
Displaying 1 - 21 of 21
Ab Initio Calculations on the Intrinsic Spin Hall Effect
The field of spintronics recently gained much interest because it promises faster, smaller and less energy consuming ...
Natural SciencesTheoretical Condensed Matter Physics
Ab-Initio Molecular Dynamics Simulations of Ultrafast Excited Graphite and Amorphous Carbon
Femtosecond laser pulses excite the electrons of matter to a high temperature whereas the ions remain mainly unaffected ...
Natural SciencesTheoretical Condensed Matter Physics
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
Balloon Estimators for Improving and Scaling the Nonparametric Off-Policy Policy Gradient
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...
Engineering SciencesComputer Science
Color Center Formation Induced by Femtosecond Lasers
The interactions of ultrashort-light pulses with solids and nanostructures is a continuously growing area due to the ...
Natural SciencesTheoretical Condensed Matter Physics
Computationally-Intensive Subproblems in FPGA-Based Accelerator Design
Field-Programmable Gate Arrays (FPGA) contain programmable logic elements that can accommodate application-specific ...
Engineering SciencesComputer Science
Constraint Space Projection Reinforcement Learning
The aim of the project is to develop a new family of optimization algorithms to handle convex constraints and evaluate ...
Engineering SciencesComputer Science
Design-Space Exploration for FPGA-Accelerators in Cloud Environments
FPGA cards are increasingly deployed to cloud data centers and made available to users as platform for the ...
Engineering SciencesComputer Science-
Evaluating and Improving Recurrent Kalman Networks
Precise models of the system dynamics are crucial for model-based control and reinforcement learning (RL) in autonomous ...
Engineering SciencesComputer Science 
First-Principles Calculations on Grain Boundaries in Nanocrystalline Graphene
The modification of intrinsic properties of graphene via defects, such as grain boundaries, has been an intense field of ...
Natural SciencesTheoretical Condensed Matter Physics
High Throughput Screening and Tuning of Magnetic Two Dimensional Materials
The demand of minimization and feasibility of integration makes two-dimensional (2D) materials remarkable in promising ...
Natural SciencesTheoretical Condensed Matter Physics
High Throughput Screening for Spin-Polarized Current in Noncollinear Materials
Like perovskite materials, antiperovskites (APVs) display many intriguing physical properties. Particularly, the ...
Natural SciencesTheoretical Condensed Matter Physics
High Throughput Screening of Topological Properties in Ferromagnets
In this work, we performed first-principles calculations to evaluate the anomalous Hall conductivity as well as the ...
Natural SciencesTheoretical Condensed Matter Physics
Interpretable Reinforcement Learning
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
Engineering SciencesComputer Science
Laser-Induced Generation Nanostructures and Nanoparticles of Different Materials in Different Media: Molecular Dynamics Investigation
The mechanisms of laser-matter interaction are of great importance for many applications including the development of ...
Natural SciencesTheoretical Condensed Matter Physics-
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
Parallelizing the Level 2A Processor for Sentinel-2 Satellite Imagery
In June 2017, the European Space Agency started systematic Level 2A processing of Sentinel- 2 acquisitions over Europe ...
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
