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Adversarial De-confounding in Individualised Treatment Effects Estimation.

, , , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 837-849. PMLR, (2023)

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Dynamic Inter-treatment Information Sharing for Heterogeneous Treatment Effects Estimation., , , , and . CoRR, (2023)A Brief Review of Hypernetworks in Deep Learning., , , , and . CoRR, (2023)Deep learning approach on information diffusion in heterogeneous networks., , and . Knowl. Based Syst., (2020)Learning Graph Representations With Maximal Cliques., , , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (2): 1089-1096 (February 2023)Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation., , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3529-3537. PMLR, (2024)Identifying influential nodes in heterogeneous networks., , , and . Expert Syst. Appl., (2020)Adversarial De-confounding in Individualised Treatment Effects Estimation., , , , , and . CoRR, (2022)GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels., , , , , and . CoRR, (2023)Collaborative Deep Forest Learning for Recommender Systems., , , and . IEEE Access, (2021)Classification of audio codecs with variable bit-rates using deep-learning methods., , , and . Digit. Signal Process., (2021)