HYBRID WORKSHOP
Bridges between Machine Learning and Quantum Information Science
Interactions entre apprentissage statistique et information quantique
9 – 10 September, 2024
Organizing Committee
Comité d’organisation
Benoit Collins (Kyoto University)
Yuka Hashimoto ( NTT Tokyo)
Hachem Kadri (Aix-Marseille Université)
Ion Nechita (CNRS, LPT Toulouse)
Interactions between machine learning and quantum information are currently receiving an increasing attention. This is driven by the desire to develop artificial intelligence that uses quantum technologies to improve the speed and performance of learning algorithms. Strong interdisciplinary collaborations are needed to face the challenges of integrating quantum information and machine learning. The goal of this workshop is to gather researchers in quantum information and machine learning together, to discuss achievements, challenges and visions at the intersection between the two fields.
TALKS
Shaheen Acheche (PASQAL) Harnessing Analog Quantum Computers for Machine Learning: Graph Similarity and Positional Encoding
Seiseki Akibue (NTT) Numerical studies on quantum state verification and random matrix
Omar Fawzi (INRIA) Learning properties of quantum states and processes
Motohisa Fukuda (Yamagata University) Random quantum channels and their uses
Martin Gärttner (Friedrich-Schiller-University Jena) Neural networks as compressed representations of quantum many body states
Tomohiro Hayase (Cluster Metaverse Lab) Random Matrices, Free Probability, and Deep Neural Networks
Sofiene Jerbi (Free University of Berlin) Shadows of quantum machine learning
Ravi Kunjwal (Aix-Marseille Université) Generalizing Bell nonlocality without global causal assumptions
SPONSORS
