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Explore the emerging field of quantum deep learning in this 43-minute talk from the EuroPython 2021 conference. Delve into the fundamentals of quantum computing and its application to deep learning, focusing on how qubits can be used to create quantum variational circuits. Learn about hybrid quantum-deep learning models that combine traditional backpropagation techniques with the probabilistic states of qubits. Discover optimization methods for these hybrid models, including Fischer approximation and Natural Gradient Descent. Examine the advantages of quantum variational deep learning circuits over traditional autograd-based circuits, and explore their applications in reinforcement learning and natural language processing. Gain insights into the democratization of quantum circuits in deep learning and understand the potential impact of this technology on the future of artificial intelligence.
