Atelier sur l'inférence causale pour les structures graphiques complexes20 au 22 juin 2018Programme |
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Le mercredi 20 juin 2018 |
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13:30 - 14:00
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Inscription (salle 5345)
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Salle(s) de réunion : 6254 |
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14:00 - 15:00
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Thomas S. Richardson
(University of Washington) Nested Markov models | Résumé |
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15:00 - 16:00
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Alexander Volfovsky
(Duke University) Causal inference on networks: from experiments to observational studies | Résumé |
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16:00 - 16:30
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Pause-café
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16:30 - 17:30
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Robin Evans
(University of Oxford) Causal model selection and local geometry | Résumé |
Le jeudi 21 juin 2018 |
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09:30 - 10:00
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Café croissants
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Salle(s) de réunion : 6254 |
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10:00 - 11:00
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Ayesha Ali
(University of Guelph) Doubly sparse regression for high dimensional data | Résumé |
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11:00 - 12:00
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Niall M. Adams
(Imperial College London) Statistical methods in cybernetwork security | Résumé |
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12:00 - 14:00
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Pause-déjeuner
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14:00 - 15:00
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Michael Hudgens
(University of North Carolina at Chapel Hill) Interference | Résumé |
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15:00 - 15:30
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Pause-café
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15:30 - 16:30
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M. Elizabeth Halloran
(University of Washington) Estimands and inference in cluster-randomized vaccine trials | Résumé |
Le vendredi 22 juin 2018 |
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09:30 - 10:00
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Café croissants
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Salle(s) de réunion : 6254 |
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10:00 - 11:00
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Shomoita Alam
(McGill University) Should a propensity score model be super? The utility of machine learning procedures for causal adjustment | Résumé |
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11:00 - 12:00
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David Benkeser (Emory University)
Marco Carone (University of Washington) Inference on vaccine sieve effects using machine learning | Résumé |
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12:00 - 14:00
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Pause-déjeuner
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14:00 - 15:00
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Nicholas Chamandy
(Lyft) Causal inference in a ridesharing network | Résumé |
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15:00 - 15:30
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Pause-café
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15:30 - 16:30
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Daniel J. Graham
(Imperial College London) The impact of speed cameras on road traffic accidents - (talk will be delivered by David A. Stephens) | Résumé |
Mise à jour: Le mardi 19 juin 2018 14:30