Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Projects
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Projekte
Displaying 1 - 25 of 25
End-to-end Learning for Multi-Embodiement Locomotion
The rapid development of robotics has enabled legged robots capable of performing highly dynamic tasks such as walking ...
Engineering SciencesComputer Science
Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis
Up-to-date contact-rich manipulation tasks remain one of the grand challenges of robotics. Equipping robots with a sense ...
IngenieurwissenschaftenInformatik-
Learning Force Distribution Estimation for the GelSight Mini Optical Tactile Sensor Based on Finite Element Analysis
Up-to-date contact-rich manipulation tasks remain one of the grand challenges of robotics. Equipping robots with a sense ...
Engineering SciencesComputer Science 
Machine Learning Application in Automotive Catalysts
The computational resources of the Lichtenberg HPC were used in this project to train physics informed machine learning ...
Natural SciencesChemical Solid State and Surface Research
Major-Minor Mean Field Multi-Agent Reinforcement Learning
Multi-agent reinforcement learning (MARL) remains difficult to scale to many agents. Recent MARL using Mean Field ...
Engineering SciencesComputer Science
Parallel Finite Element Methods for Complex Flows of Complex Fluids
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
Engineering SciencesHeat Energy Technology, Thermal Machines, Fluid Mechanics
Parameter-Efficient Tuning of Pretrained Visual-Language Models in Multitask Robot Learning
General-purpose intelligent robots are expected to simultaneously handle multiple tasks while interpreting various ...
Engineering SciencesComputer Science-
Amortized Variational Inference by Policy Search
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
Engineering SciencesComputer Science 
Deep Implicit Collision Probability Fields
In robotic applications such as autonomous driving and whole-body control, ensuring safety is of utmost importance ...
Engineering SciencesComputer Science
Deep Reinforcement Learning for Robotics
Robotics platforms can massively benefit from novel Deep Reinforcement Learning approaches. However, robotics have ...
Engineering SciencesComputer Science
Detecting Suitcase Damages With Artificial Intelligence – IT-Project Lufthansa
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Engineering SciencesComputer Science-
Gradient-Based Variational Inference by Policy Search
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
Engineering SciencesComputer Science -
Impact of Multipath-Effects on Acoustic Keylogging Systems
Acoustic keylogging describes a category of side-channel attacks that recover typed keystrokes from audio-streams of ...
Engineering SciencesComputer Science 
Investigating the Machine Learning-based Cryptanalysis of Lightweight Block Ciphers
Lightweight Cryptography is about developing and analyzing algorithms that provably obtain security goals, such as ...
Engineering SciencesComputer Science
Learning to Plan
Motion planning is a crucial component of autonomous robot systems. It addresses the problem of finding a feasible ...
Engineering SciencesComputer Science-
Neural Scene Understanding For Robotics
Autonomous robots need to be able to identify and recognize objects in a scene. For this crucial task we need to ...
Engineering SciencesComputer Science 
Policy Optimization with Learning and Planning in Continuous Spaces
Planning algorithms have shown impressive performance in many domains such as chess and Go. In particular, Monte Carlo ...
Engineering SciencesComputer Science
Predicting Human Similarity Judgments Using Normalizing Flows
Recent work has shown that deep neural networks are able to predict human similarity judgments with high accuracy (e.g ...
Humanities and Social Sciences
Scalable Task-Driven Robotic Swarm Control via Collision Avoidance and Learning Mean-Field Control
In recent years, reinforcement learning and its multi-agent analogue have achieved great success in solving various ...
Engineering SciencesComputer Science-
Scientific Machine Learning for Chemical Kinetics
Detailed multi-scale modelling provides in-depth insights into the complex phenomena of catalytic systems that typically ...
Engineering SciencesProcess Engineering, Technical Chemistry 
The Physical Informed Machine Learning Guided Material Design and Characterization
X-ray Absorption Spectroscopy (XAS) is a pivotal technique in material research, requiring numerous sampling points for ...
Engineering SciencesMaterials Science
Combining Regenerative and Degenerative Methods in Growing Neural Networks
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
Engineering SciencesComputer Science-
Learning for Decentralized, Long-Horizon Manipulation
Achieving long-horizon dexterous manipulation remains a challenging problem in robotics. There exists a long history of ...
Engineering SciencesSystems Engineering -
Visuomotor Control of Pouring Liquids
Natural visuomotor control tasks such as pouring liquids into cups are trivial for humans but are challenging to model ...
Life SciencesNeurosciences 
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
