Quantum Backpropagation and Information Reuse in Neural Networks

Join a Qiskit Quantum Seminar where postdoctoral researcher Amira Abbas explores the fascinating intersection of quantum computing and deep learning, specifically focusing on quantum backpropagation and information reuse. Delve into how modern deep learning's success relies on training neural networks through backpropagation's clever reuse of intermediate information, and discover recent developments challenging the conventional wisdom about quantum measurement collapse. Learn about shadow tomography's role in potentially achieving backpropagation scaling for parameterized quantum models, a crucial advancement for their large-scale implementation. Benefit from Abbas's extensive expertise gained through her work at the University of Amsterdam, QuSoft, Google Quantum AI, and IBM, as she presents this 56-minute technical discussion on bridging classical deep learning techniques with quantum computing systems.