Search Results for author:
Found 3 papers, 2 papers with code
Local Constraint-Based Causal Discovery under Selection Bias
We consider the problem of discovering causal relations from independence constraints selection bias in addition to confounding is present.
Boosting Local Causal Discovery in High-Dimensional Expression Data
We study the performance of Local Causal Discovery (LCD), a simple and efficient constraint-based method for causal discovery, in predicting causal effects in large-scale gene expression data.
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
An important goal common to domain adaptation and causal inference is to make accurate predictions when the distributions for the source (or training) domain(s) and target (or test) domain(s) differ.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
