DLR Institute Team for AI Safety and Security at ESANN 2025 From left: Lautaro Hickmann, Dr Fabian Fischbach, Gustav Jäger, Dr Hans-Martin Rieser, Dr Markus Lange
Scientific Session on Quantum Computers and Quantum-Like Methods for Machine Learning
The intersection of quantum computing and artificial intelligence offers a whole new perspective on the future of machine learning. At the 33rd European Symposium on Artificial Neural Networks (ESANN 2025), the DLR Institute for AI Safety and Security presented the latest findings on this future prospect topic.
The Institute-led scientific session focused on innovative approaches to extend and improve classical AI systems through quantum technology. Topics covered include purely classic machine learning approaches inspired by quantum physics, such as classic preprocessing of quantum AI, efficient coding strategies, quantum classic hybrid models, and tensor networks.
Four highlight topics show the possibilities of quantum methods
Our session focused on four important topics that demonstrate the potential of quantum methods in AI research.
2. Tensor Networks (Density Matrix Renormalization Groups) with Efficient Quantum Machine Learning Normalization Constraints using DMRG: An approach that can significantly improve the computational efficiency of quantum AI systems.
Quantum tensor network learning using DMRG
3. The innovative hybrid quantum annealing approach to predict excavator prices developed by Fraunhofer IAO is an example of a practical application of quantum methods in industry.
Puntum Quantum Annealing-Based Features Selection
“ESANN 2025 provided the ideal platform for a scientific exchange with key figures in the international AI community,” explained the head of the DLR session. “In particular, the hybrid quantum AI approach, combining classical methods and quantum technology, was fulfilled with great interest.”
Interdisciplinary research into safe AI technology
Intensive discussions on quantum tensor networks and quantum-inspired methods opened up new research perspectives and created valuable contacts with other experts. These findings will be directly incorporated into the future work of the Institute.
The DLR Institute for AI Safety and Security develops technologies that enable the safe and reliable use of AI through interdisciplinary collaborations, including quantum methods. Esann’s findings can help to actively shape the future of AI.
The Institute looks forward to further its research and investigating the possibilities of quantum AI in the growing quantum machine learning (QML) community.
