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Physical Perspectives on Modern Computation

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If you have a question about this talk, please contact Nicolai Baldin.

Contemporary approaches to tasks in computation (e.g. machine learning, optimisation, Bayesian statistics) draw rich and varied inspiration from models of physics. In this talk, I will outline some examples where this approach has proven fruitful, as well as more general conceptual links between physical thinking and (statistical) computation. I will then attempt to give a convincing overview of why such methods succeed, and why we should expect them to continue to offer insight into such tasks going forward.

This talk is part of the Cambridge Analysts' Knowledge Exchange series.

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