26 citations · 76 across the 14 of their papers we have counts for
4 papers · 1 filter
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms
Trent Kyono, Yao Zhang, Alexis Bellot +1
Missing data is an important problem in machine learning practice. Starting from the premise that imputation methods should preserve the causal structure of the data, we develop a…
Neural graphical modelling in continuous-time: consistency guarantees and algorithms
Alexis Bellot, Kim Branson, Mihaela van der Schaar
The discovery of structure from time series data is a key problem in fields of study working with complex systems. Most identifiability results and learning algorithms assume the u…
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding
Alexis Bellot, Mihaela van der Schaar
Unobserved confounding is one of the greatest challenges for causal discovery. The case in which unobserved variables have a widespread effect on many of the observed ones is parti…
Policy Analysis using Synthetic Controls in Continuous-Time
Alexis Bellot, Mihaela van der Schaar
Counterfactual estimation using synthetic controls is one of the most successful recent methodological developments in causal inference. Despite its popularity, the current descrip…