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Seth Flaxman

Seth Flaxman, Ph.D., is Associate Professor in the Department of Computer Science at the University of Oxford.

A winner of the Samsung AI Researcher of the Year award (2020), Flaxman has a Ph.D. in machine learning and public policy from Carnegie Mellon University.

He was previously faculty at Imperial College London where he led landmark studies on the effectiveness of non-pharmaceutical interventions during the first wave of the Covid-19 pandemic in Europe (Flaxman et al, Nature, 2020) and on pandemic-associated orphanhood (Hillis et al, Lancet, 2021).

Within the field of machine learning, he works on statistical machine learning methods for spatiotemporal data, Bayesian methods, and kernel methods and has published in NeurIPS, ICML, KDD, AISTATS, and UAI.

You can visit his personal webpage here.

Google Scholar Citation Page

Seth's Seminars

Advanced Machine Learning

This seminar assumes a basic familiarity with machine learning and covers statistical machine learning, Bayesian machine learning, kernel methods and Gaussian processes, Bayesian probabilistic programming with MCMC and variational inference, Bayesian Additive Regression Trees, deep generative modeling with variational autoencoders,...

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Machine Learning

Machine learning has emerged as a major field at the intersection of statistics and computer science where the goal is to create reliable and flexible predictive models. This seminar offers a thorough introduction to supervised machine learning methods. Topics covered...

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