7 papers
Testing Partially-Identifiable Causal Queries Using Ternary Tests
Sourbh Bhadane, Joris M. Mooij, Philip Boeken +1
We consider hypothesis testing of binary causal queries using observational data. Since the mapping of causal models to the observational distribution that they induce is not one-t…
Foundations of Structural Causal Models with Latent Selection
Leihao Chen, Onno Zoeter, Joris M. Mooij
Three distinct phenomena complicate statistical causal analysis: latent common causes, causal cycles, and latent selection. Foundational works on Structural Causal Models (SCMs), e…
CLAX: Fast and Flexible Neural Click Models in JAX
Philipp Hager, Onno Zoeter, Maarten de Rijke
CLAX is a JAX-based library that implements classic click models using modern gradient-based optimization. While neural click models have emerged over the past decade, complex clic…
Conditional Forecasts and Proper Scoring Rules for Reliable and Accurate Performative Predictions
Philip Boeken, Onno Zoeter, Joris M. Mooij
Performative predictions are forecasts which influence the outcomes they aim to predict, undermining the existence of correct forecasts and standard methods of elicitation and esti…
Unidentified and Confounded? Understanding Two-Tower Models for Unbiased Learning to Rank (Extended Abstract)
Philipp Hager, Onno Zoeter, Maarten de Rijke
Additive two-tower models are popular learning-to-rank methods for handling biased user feedback in industry settings. Recent studies, however, report a concerning phenomenon: trai…
Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
Sourbh Bhadane, Joris M. Mooij, Philip Boeken +1
Reasoning about fairness through correlation-based notions is rife with pitfalls. The 1973 University of California, Berkeley graduate school admissions case from Bickel et. al. (1…