Stochastic Analysis & Algorithms: From numerics for SDEs to Langevin algorithms

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• Sotirios Sabanis (University of Edinburgh)
• Thursday 27 June 2024, 15:00-16:50
• External.

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DMLW02 - Summer school on fundamentals and applications of diffusion models

In recent years, diffusion-based algorithms have gained significant popularity due to their extensive application in sampling and non-convex optimization. These algorithms are frequently conceptualized as numerical schemes for stochastic differential equations (SDEs), a perspective that enables the utilization of advanced tools from modern probability theory and stochastic analysis for their analysis. We will review critical aspects of the analysis of these numerical methods applied to random systems, and will provide important comparisons with stochastic gradient methods commonly employed in machine learning and artificial intelligence.

This talk is part of the Isaac Newton Institute Seminar Series series.

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