16 citations · 17 across the 5 of their papers we have counts for
3 papers · 1 filter
Causal Discovery Under Hard Selection Bias: A New Robust Score-Matching Approach
Yiwen Qiu, Francesco Montagna, Shimeng Huang +1
Selection bias is a difficult yet widespread problem in causal discovery, occurring whenever non-random selection processes lead to data that is not representative of the underlyin…
Towards a holistic understanding of Selection Bias for Causal Effect Identification
Yiwen Qiu, Filip Kovačević, Shimeng Huang +2
Selection bias is pervasive in observational studies. For example, large scale biobanks data can exhibit ``healthy volunteer bias'' when respondents are healthier and of higher soc…
Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
Shimeng Huang, Matthew Robinson, Francesco Locatello
Mendelian Randomization (MR) is a prominent observational epidemiological research method designed to address unobserved confounding when estimating causal effects. However, core a…