CEN-IBS/GMDS Invited Session on "Causal Inference and Machine Learning"

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This is the virtual invited session "Causal Inference and Machine Learning" for the 2020 joint conference of the GMDS & CEN-IBS

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Note: the event is free, but you need to register via this eventbrite site.

28 September

Programme (CEST, Berlin time):

  • Introduction
  • 15:00-15:20: Karla Diaz-Ordaz, London School of Hygene and Tropical Medicine, UK: "Machine Learning estimation of Causal estimands: why and how"
  • 15:25-15:45: Jonas Peters, Dpt. of Mathematical Sciences, University of Copenhagen, Denmark: "The hardness of conditional independence testing"
  • short break
  • 15:55-16:15: Oliver Dukes, Dpt. of Applied Mathematics, Computer Science and Statistics, Ghent University, Belgium: "Assumption-lean inference for generalised linear model parameters"
  • 16:20-16:50: Andrea Rotnitzky, Dpt. of Economics, Universidad Torcuato Di Tella, Argentina; and Harvard School of Public Health, US: "Optimal adjustment sets in non-parametric graphical models"
  • open discussion

Organisers: Stijn Vansteelandt, Ghent University, UK; and Vanessa Didelez, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany

To attend: please register through this evenbrite site. A few days before the session, you will receive a link allowing you to participate.

Note: this event will be live and will not be recorded.

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Organiser Vanessa Didelez

Organiser of CEN-IBS/GMDS Invited Session on "Causal Inference and Machine Learning"

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