2 citations · 4 across the 4 of their papers we have counts for
4 papers
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…
GraphITE: Estimating Individual Effects of Graph-structured Treatments
Shonosuke Harada, Hisashi Kashima
Outcome estimation of treatments for target individuals is an important foundation for decision making based on causal relations. Most existing outcome estimation methods deal with…
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…
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…