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Learn about conditional simulation techniques using entropic optimal transport in this 29-minute conference talk delivered at the Fields Institute. Explore advanced mathematical concepts connecting optimal transport theory with stochastic processes and their applications in conditional simulation problems. Discover how entropic regularization can be applied to optimal transport frameworks to enable efficient computational approaches for generating conditional samples. Examine the theoretical foundations underlying these methods and understand their practical implementations in various scientific and engineering contexts. Gain insights into the intersection of optimal transport theory, probability theory, and computational mathematics through detailed mathematical exposition and examples. Access comprehensive background materials and related research through the provided abstract and conference series on optimal transport applications in stochastics and projections.
