13 citations · 15 across the 3 of their papers we have counts for
5 papers
Bayesian Modeling of Marketing Attribution
Ritwik Sinha, David Arbour, Aahlad Manas Puli
In a multi-channel marketing world, the purchase decision journey encounters many interactions (e.g., email, mobile notifications, display advertising, social media, and so on). Th…
Causal Estimation with Functional Confounders
Aahlad Puli, Adler J. Perotte, Rajesh Ranganath
Causal inference relies on two fundamental assumptions: ignorability and positivity. We study causal inference when the true confounder value can be expressed as a function of the…
X-CAL: Explicit Calibration for Survival Analysis
Mark Goldstein, Xintian Han, Aahlad Puli +2
Survival analysis models the distribution of time until an event of interest, such as discharge from the hospital or admission to the ICU. When a model's predicted number of events…
General Control Functions for Causal Effect Estimation from Instrumental Variables
Aahlad Manas Puli, Rajesh Ranganath
Causal effect estimation relies on separating the variation in the outcome into parts due to the treatment and due to the confounders. To achieve this separation, practitioners oft…
Removing Hidden Confounding by Experimental Grounding
Nathan Kallus, Aahlad Manas Puli, Uri Shalit
Observational data is increasingly used as a means for making individual-level causal predictions and intervention recommendations. The foremost challenge of causal inference from…