seminar series: Causal Inference and Machine Learning
- When
- 28-09-2020 from 15:00 to 17:00
- Where
- Virtual
- Organizer
- Vanessa Didelez
- Contact
- cen-ml-causal@leibniz-bips.de
- Website
- https://www.eventbrite.de/e/cen-ibsgmds-invited-session-on-causal-inference-and-machine-learning-tickets-116222778459
Virtual Satellite Invited Session of the CEN-IBS and GMDS 2020
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.