Graduate Student / Postdoc Seminar

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Conditional probability simulation through optimal transport

Speaker: Esteban Tabak, Courant Institute of Mathematical Sciences

Location: Warren Weaver Hall 1302

Date: Friday, April 26, 2019, 1 p.m.

Synopsis:

Conditional probability estimation provides data-based answers to all kinds of critical questions, such as the expected response of specific patients to different medical treatments, weather and climate forecasts, and the effect of political measures on the economy. In the complex systems behind these examples, the outcome of a process depends on many and diverse factors and is probabilistic in nature, due in part to our ignorance of other relevant factors and to the chaotic nature of the underlying dynamics.

I will describe a general procedure for the estimation and simulation of conditional probabilities, based on the removal of the effect of covariates through a data-based, generalized optimal transport barycenter problem, formulated as an adversarial game.