2 papers
cs.LG2024
Federated Causal Discovery from Heterogeneous Data
Loka Li, Ignavier Ng, Gongxu Luo +5
Conventional causal discovery methods rely on centralized data, which is inconsistent with the decentralized nature of data in many real-world situations. This discrepancy has moti…
cs.LG2023
Advancing Counterfactual Inference through Nonlinear Quantile Regression
Shaoan Xie, Biwei Huang, Bin Gu +2
The capacity to address counterfactual "what if" inquiries is crucial for understanding and making use of causal influences. Traditional counterfactual inference, under Pearls' cou…