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Solving a combinatorial optimization problem with a hybrid quantum-classical algorithm.

Simulation env based on Brax / MuJoCo for robotic assembly tasks.

Platform-independent SGX client bindings from the asylo framework.

Sample webapp for Cloud workshop at Fraunhofer ATIM 2018 in Dresden

The demonstration illustrates the generation of a quantum feature map for a simple regression problem. Reinforcement learning techniques are used, visualizing the decision process of the AI agent through a simple visualization of the quantum circuit creation. We show how to load, train and test the model. The results show a feature map design tailored to the problem.

This is the code developed by Dr.-Ing. Dominique Koster and contributed to by Dr. Mariam R. Rizkallah for the workshop "Data Reconciliation: Integration of Electrochemical Data and Optical Sensor Data for Health Diagnostics of Lithium-Ion Batteries" https://www.bremen-research.de/data-train/courses/course-details?event_id=88

Excel macro for handling XML output from B1500A Semiconductor Device Analyzer

Minimales CMake-C++ Projekt mit beispielhafter Gitlab-CI-Pipeline.

Project group: 3D Environment Based Intelligent Systems Engineering of Advanced Systems (BATMAN), University of Paderborn/Fraunhofer IEM Paderborn