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stat.ML2025
The Hardness of Validating Observational Studies with Experimental Data
Jake Fawkes, Michael O'Riordan, Athanasios Vlontzos +2
Observational data is often readily available in large quantities, but can lead to biased causal effect estimates due to the presence of unobserved confounding. Recent works attemp…
stat.ML2024
Contrastive representations of high-dimensional, structured treatments
Oriol Corcoll Andreu, Athanasios Vlontzos, Michael O'Riordan +1
Estimating causal effects is vital for decision making. In standard causal effect estimation, treatments are usually binary- or continuous-valued. However, in many important real-w…