Atelier sur la découverte de la structure causale à haute dimension

25 au 27 juin 2018

Programme

 

Le lundi 25 juin 2018

09:00 - 09:30
Inscription (salle 5345) et café-croissants (salle 6245)


09:30 - 10:15
Yang Ning
(Cornell University )
High-Dimensional propensity score estimation via covariate balancing
Résumé
10:15 - 10:30
Pause-café
10:30 - 11:15
Denis Talbot
(Université Laval)
A Bayesian causal effect estimation algorithm for adjusting for confounding
Résumé
11:15 - 12:00
Arvid Sjölander
(Karolinska Institutet)
The case-time-control design. Basic theory and extensions
Résumé
12:00 - 13:30
Pause-déjeuner
13:30 - 14:15
Thomas S. Richardson
(University of Washington)
Structural nested mean models for binary treatments and outcomes
Résumé
14:15 - 15:00
Ali Shojaie
(University of Washington)
The reduced PC-Algorithm: Improved causal structure learning in high dimensions
Résumé
15:00 - 15:30
Pause-café
15:30 - 16:45
Nicolai Meinshausen
(ETH Zürich)
Distributional robustness from a causal point of view
Résumé

 

Le mardi 26 juin 2018

09:00 - 09:30
Café croissants


09:30 - 10:15
Peter Schulam
(Johns Hopkins University)
Reliable decision-support using counterfactual models
Résumé
10:15 - 10:30
Pause-café
10:30 - 11:15
Julian Wolfson
(University of Minnesota)
Covariate selection with group lasso and doubly robust estimation of causal effects
Résumé
11:15 - 12:00
Susan Shortreed
(Kaiser Permanente Washington Health Research Institute)
Variable selection for causal inference: outcome-adaptive lasso
Résumé
12:00 - 13:30
Pause-déjeuner
13:30 - 14:15
Eric Laber
(NC State University )
Optimal treatment allocations in space and time for online control of an emerging infectious disease
Résumé
14:15 - 15:00
James Robins
(Harvard School of Public Health)
15:00 - 15:30
Pause-café
15:30 - 16:45
Min-ge Xie
(Rutgers University)
Uncertainty quantification of treatment regime in precision medicine by confidence distributions
Résumé

 

Le mercredi 27 juin 2018

09:00 - 09:30
Café croissants


09:30 - 10:15
Guido W. Imbens
(Stanford Graduate School of Business)
Matrix completion methods for causal panel data models
Résumé
10:15 - 10:30
Pause-café
10:30 - 11:15
Stefan Wager
(Stanford University)
Quasi-oracle estimation of heterogeneous causal effects
Résumé
11:15 - 12:00
Walter Dempsey
(Harvard University)
The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatments
Résumé
12:00 - 13:30
Pause-déjeuner
13:30 - 14:15
Michael Rosenblum
(Johns Hopkins Bloomberg School of Public Health)
Estimating the protective effect of longitudinal drug concentration in pre-exposure prophylaxis for HIV prevention
Résumé
14:15 - 15:00
Mireille Schnitzer
(Université de Montréal)
Longitudinal variable selection in causal inference with collaborative targeted minimum loss-based estimation
Résumé
15:00 - 15:30
Café