Machine learning for causal inference

Please join us for our next Wits SEF Brown Bag (BB) Seminar, presented by Dr Jason Hartford.

We are honoured to host Dr Jason Hartford (https://jhartford.github.io/) from the University of Manchester, who will present his work on the use of machine learning for causal inference. Dr Hartford will provide an introduction to machine learning as well as report on some of his latest research and developments in the use of machine learning.

Abstract

Machine learning offers a large new set of tools that enable more flexible estimation of models to answer existing causal questions, and the prospect of answering new questions. In this talk, I will give an overview of the computer science perspective on causal inference and how it connects with popular techniques in econometrics. I will illustrate with examples from my own work on using deep learning for nonparametric instrumental variable regression and discuss some of my more recent work on representation learning questions that aim to deal with unstructured data like images and text.

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