BlogApplication Training and adapting AI for flood prediction Adrian Holt, Hannes Behnen, 29. October 2026 How can AI accelerate flood prediction? FloodWaive and WestAI explored efficient training and regional adaptation. The AI-supported flood forecasting system is already in use in StädteRegion Aachen....
BlogResearch qubolite: A Toolbox for Working with QUBO Thore Gerlach, 31. January 2024 Quadratic unconstrained binary optimization (QUBO) problems appear in many different domains such as Machine Learning and Data Mining. We present our light-weight and feature-rich Python package qubolite for working with QUBO....
BlogResearch Explaining Gates in Quantum Circuits with Shapley Values Sascha Mücke, 22. March 2023 By applying Shapley values to quantum computing, Lamarr scientists seek to explain the role of specific gates in a quantum circuit and give insights into how quantum machine learning models work....
BlogApplication Preparing for the quantum age with the IAIS Evo Annealer Thore Gerlach, 02. November 2022 The IAIS Evo Annealer is a bridging technology for Quantum Computing. With its energy efficiency and the ability to solve large mathematical problems, it can already be used in practice....
BlogResearch Quantum random numbers in Machine Learning Sascha Mücke, 27. October 2021 Due to their stochastic behavior, qubits (quantum bits) can be used as a source of (true) random numbers in Machine Learning. ML2R (now the Lamarr Institute) researchers investigated the use of quantum random numbers to initialize Machine Learning models....
BlogResearch Evolutionary Optimization of Quantum Circuits Sascha Mücke, 12. May 2021 Evolutionary optimization is a real alternative to gradient-based methods, as it can be used more flexibly in different application scenarios. Lamarr researchers used evolutionary algorithms to optimize quantum computer circuits....
