Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 30 of 35
Ab Initio No-Core Shell Model
The prime goal of ab initio nuclear structure theory is the description of correlated systems of many nucleons based on ...
Natural SciencesParticles, Nuclei and Fields
Automatic Code Parallelization
The Software-Factory 4.0 (SF4.0) is a 4-year LOEWE1 project funded by the German State of Hesse and involves several ...
Engineering SciencesComputer Science
Correctness Checking of MPI Derived Datatypes Using TypeART
The message passing interface (MPI) is the de-facto standard for distributed high performance computing. However, it ...
Engineering SciencesComputer Science
Designing an Efficient Neural Architecture Search
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
Engineering SciencesComputer Science
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions
Trajectory optimization and model predictive control are essential techniques underpinning advanced robotic applications ...
Engineering SciencesComputer Science
Fully Open-Shell Medium-Mass Nuclei and Electromagnetic Observables for Ab Initio Nuclear Structure II
The ab initio description of nuclear structure phenomena has progressed tremendously over the past years. In particular ...
Natural SciencesParticles, Nuclei and Fields-
Image Analysis and Calibration of High Dimensional Deformable Cell Models in Complex Geometries Using Advanced Interaction Schemes
Organ-like three-dimensional cell aggregates developed in the laboratory represent versatile cellular models for drug ...
Life SciencesBasic Research in Biology and Medicine 
Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System
Normative computational models of human sensorimotor behavior based on optimal feedback control with signal-dependent ...
Life SciencesNeurosciences-
Inverse Reinforcement Learning by Matching Feature Distributions
Reinforcement Learning is a powerful approach to achieve optimal behaviour. However, it typically requires a manual ...
Engineering SciencesComputer Science 
Learning Physically Interactive Behaviours for Human-Robot Interaction
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human’s actions ...
Engineering SciencesComputer Science
Matrix Elements of New Families of Chiral Interactions
The goal of ab initio nuclear structure theory is the description of nuclei from first principles without uncontrolled ...
Natural SciencesParticles, Nuclei and Fields
Measure-Valued Derivatives for Reinforcement Learning
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
Engineering SciencesComputer Science
Modeling of Large Proteins in DNA Repair
DNA-PKcs is a gateway protein of the Non-Homologous End Joining DNA Repair Pathway. Which is the process of repairing ...
Natural SciencesEngineering SciencesComputer Science
Molecular Dynamics Study of the Sodium/Potassium Channels HCN
Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons ...
Life SciencesBasic Research in Biology and Medicine-
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 
Precision Scale Setting Directly at High Temperatures Using Gradient Flow
The overarching goal of our research project is the determination of the QCD topological susceptibility Xtop(T) at very ...
Natural SciencesParticles, Nuclei and Fields
Scalability of OpenMP
This project is concerned with promoting a more efficient usage of the HPC Systems. The two major technologies used to ...
Engineering SciencesComputer Science
When to Trust Your Model in Model-based Value Expansion?
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
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
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
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 
Interpretable Reinforcement Learning
Deep Reinforcement Learning can solve difficult high dimensional tasks, by exploiting the expressive representation ...
Engineering SciencesComputer Science
Large-Scale Configuration Interaction for Ab Initio Nuclear Structure
The goal of ab initio nuclear structure theory is the description of correlated systems of many nucleons based on the ...
Natural SciencesParticles, Nuclei and Fields
Lifetime Portfolio Choice and Optimal Retirement Decisions
Millions of European and American workers are increasingly asked to accumulate pension assets. In order to augment ...
Humanities and Social SciencesEconomics-
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 
Molecular Dynamics Study of the Sodium/Potassium Channels HCN
Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons ...
Life SciencesBasic Research in Biology and Medicine-
Multi-Label Rule Learning
This project aimed at solving multi-label classification problems using rule learning algorithms. Multi-label ...
Engineering SciencesComputer Science
