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Machine Learning and Finite Elements

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If you have a question about this talk, please contact Kimberly Cole.

The Cambridge ELLIS Unit has started a Seminar Series that will include talks by leading researchers in the area of machine learning and AI. Our first speaker will be Prof. Mark Girolami. Details of his talk can be found below.

Title: “Machine Learning and Finite Elements’”

Abstract: The finite element method (FEM) is one of the great triumphs of applied mathematics, numerical analysis and software development. Recent developments in sensor and signalling technologies enable the phenomenological study of systems. The connection between sensor data and FEM is restricted to solving inverse problems placing unwarranted faith in the fidelity of the mathematical description of the system. If one concedes mis-specification between generative reality and the FEM then a framework to systematically characterise this uncertainty is required. This talk will present a statistical construction of the FEM which systematically blends mathematical description with observations.

This talk is part of the Cambridge Ellis Unit series.

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