NEASQC webinar - 04/06/2024 - Quantum machine learning and industrial applications

NEASQC is organising a series of interactive webinars to share our findings with the quantum computing community. Each month NEASQC experts present an Open Source library available in the NEASQC GitHub or a technique they investigated, and answer your questions.
In June, we present some outcomes of the NEASQC use case on Inventory Management.
Abstract: While the developments in quantum computing systems offer suggest that quantum computers capable of some beyond-classical applications are within reach, the genuine impact quantum computers realize will ultimately depend on the real-world applications they offer advantages for. This remains an ever more urgent and open question in the field. In this talk we will discuss and contrast the recent progress in quantum machine learning: progress in theory clarifying how to run quantum algorithms on limited devices and provable advantages in machine learning tasks, on the one hand; and the studies we have performed in applications of these methodologies in simple but concrete use cases involving inventory management on the other.
Speaker: Prof.dr. Vedran Dunjko, University of Leiden
Vedran Dunjko’s research interest lies in the intersection of computer science and quantum physics, including quantum computing and quantum cryptography. Over the course of the last few years, he has been focusing on the interplay between quantum computing, machine learning, and artificial intelligence. He is professor of quantum computing at Leiden University, and lead of the Leiden applied Quantum algorithms Initiative.
Related publications
Deliverable: D5.5 Implementation of QRL algorithm on real architecture (report)
Publication: Quantum Machine Learning Beyond Kernel Methods (The Journal of Chemical Physics)

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