Classical ML for Quantum Problems - IPAM at UCLA

Classical ML for Quantum Problems - IPAM at UCLA

Explore the intersection of classical machine learning and quantum problems in this comprehensive lecture presented by Hsin-Yuan Huang (Robert) from Google Quantum AI. Delivered at the Institute for Pure & Applied Mathematics (IPAM) at UCLA, this 79-minute talk is part of the Mathematical and Computational Challenges in Quantum Computing Tutorials series. Delve into cutting-edge research that applies classical machine learning techniques to address complex quantum challenges. Gain insights into how these approaches can potentially revolutionize quantum computing and related fields. Suitable for researchers, students, and professionals interested in the convergence of machine learning and quantum science.