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In this demonstration, we present a Quantum Alternating Algorithm designed to address Mixed Integer Linear Problems (MILP). The algorithm's efficacy is showcased through the resolution of an energy use case, employing CPU and GPU quantum simulators, as well as the IBM Quantum System at Ehningen.

[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning

Smart Farming User Console

SICK - Lidar Localization Software

Project implemented as part of Master Thesis: Generative AI Driven Systems Engineering Competency Assessment. Developed By: Derik Roby (derik.roby@outlook.com) Supervisor: Ulf Könemann Professor: Prof. Dr.-Ing. Roman Dumitrescu

Here we perform a hybrid, Grover based optimization to find the single network parameter change that leads to the largest reduction of the critical failure probability in a cascading network

scrapping scooter data

A demonstrator for the Sequoia End-to-End project which shows how scenario-based route planning to safeguard automotive driving functions can be implemented to run on a quantum computer