31 citations · 64 across the 7 of their papers we have counts for
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Inferring the Direction of a Causal Link and Estimating Its Effect via a Bayesian Mendelian Randomization Approach
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an ex…
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models
Ioan Gabriel Bucur, Tom Claassen, Tom Heskes
The recent availability of huge, many-dimensional data sets, like those arising from genome-wide association studies (GWAS), provides many opportunities for strengthening causal in…
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
Tom Heskes, Evi Sijben, Ioan Gabriel Bucur +1
Shapley values underlie one of the most popular model-agnostic methods within explainable artificial intelligence. These values are designed to attribute the difference between a m…