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Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data.

, , , , , and . ACM Trans. Knowl. Discov. Data, 18 (3): 48:1-48:21 (April 2024)

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Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data., , , , , and . ACM Trans. Knowl. Discov. Data, 18 (3): 48:1-48:21 (April 2024)SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training., , , , and . ECML/PKDD (4), volume 13716 of Lecture Notes in Computer Science, page 400-417. Springer, (2022)A Study on the Impact of Non-confounding Covariates on the Inferential Performance of Methods based on the Potential Outcome Framework., , and . CoRR, (2023)Identification of Cancer Development Related Pathways Based on Co-Expression Analyses., , , , , and . BIBM, page 108-114. IEEE, (2020)De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network., , , , and . CoRR, (2023)Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name., , , , and . Genom. Proteom. Bioinform., 17 (3): 273-286 (2019)Identification of key somatic oncogenic mutation based on a confounder-free causal inference model., , , and . PLoS Comput. Biol., 18 (9): 1010529 (September 2022)Improve Robustness of Graph Neural Networks: Multi-hop Neighbors Meet Homophily-based Truncation Defense., , , and . IJCNN, page 1-8. IEEE, (2023)Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks., , , , , , and . PloS one, (2014)The bioinformatics toolbox for circRNA discovery and analysis., , , , , , and . Briefings Bioinform., 22 (2): 1706-1728 (2021)