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cs.LG2024
Treatment Effect Estimation for Graph-Structured Targets
Shonosuke Harada, Ryosuke Yoneda, Hisashi Kashima
Treatment effect estimation, which helps understand the causality between treatment and outcome variable, is a central task in decision-making across various domains. While most st…
cs.LG2020
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation
Shonosuke Harada, Hisashi Kashima
Individual treatment effect (ITE) represents the expected improvement in the outcome of taking a particular action to a particular target, and plays important roles in decision mak…
cs.LG2018
Dual Convolutional Neural Network for Graph of Graphs Link Prediction
Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki +4
Graphs are general and powerful data representations which can model complex real-world phenomena, ranging from chemical compounds to social networks; however, effective feature ex…