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QI: Fachverband Quanteninformation

QI 3: Quantum Machine Learning

Montag, 6. März 2023, 11:00–13:00, B305

	11:00	QI 3.1	Hauptvortrag: Characterising quantum device variability with machine learning — •Natalia Ares
	11:30	QI 3.2	The application of quantum neural networks in function approximation — •David Kreplin and Marco Roth
	11:45	QI 3.3	Parameterized quantum circuits for reinforcement learning of classical rare dynamics — Alissa Wilms, •Laura Ohff, Andrea Skolik, David A. Reiss, Sumeet Khatri, and Jens Eisert
	12:00	QI 3.4	Optimal storage capacity of quantum Hopfield neural networks — •Lukas Bödeker, Eliana Fiorelli, and Markus Müller
	12:15	QI 3.5	Quantum kernel methods for regression — •Jan Schnabel
	12:30	QI 3.6	Renormalisation through the lens of QCNNs — •Nathan A. McMahon, Petr Zapletal, and Michael J. Hartmann
	12:45	QI 3.7	Quantum Gaussian Processes for Bayesian Optimization — •Frederic Rapp and Marco Roth