Abstract: The success of modern deep learning hinges on the ability to train neural networks at scale. Through clever reuse of intermediate information, backpropagation facilitates training through gradient computation at a total cost roughly proportional to running the function, rather than incurring an additional factor proportional to the number of parameters - which can now …

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Title of talk: Universal cooling dynamics toward a quantum critical point Speaker: Emma King (present affiliation: University of Saarland, Saarbrücken, Germany; the work I will present was done at Stellenbosch University, Stellenbosch, South Africa). Abstract: Curiosity surrounding concepts such as critical phenomena, scaling laws and universality in out-of-equilibrium settings has inspired vibrant research in the …

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https://www.youtube.com/watch?v=A7-zuKanVbQ&t=1290s

Title of talk: Quantum work statistics at strong reservoir coupling. Speaker: Dr Ahsan Nazir (University of Manchester, United Kingdom). Abstract: Calculating the stochastic work done on a quantum system while strongly coupled to a reservoir is a formidable task, requiring the calculation of the full eigenspectrum of the combined system and reservoir. In this talk …

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Title of talk: Structural crossovers in trapped ions dispersively coupled to optical cavities. Speaker: Alan Kahan. Abstract: We consider an optomechanical system composed of a trapped ion dispersively coupled to a single mode of a pumped optical cavity. We focus on a parameter range that exhibits bistability of different configurations in the semiclassical description. This …

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At today's Group Meeting Chanelle will speak about Qunatum Logistic Regression. Her presentation will be based on the  paper https://arxiv.org/abs/1906.03834v2