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Uplift Modeling based on Graph Neural Network Combined with Causal
  Knowledge

Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge

14 November 2023
Haowen Wang
Xinyan Ye
Yangze Zhou
Zhiyi Zhang
L. Zhang
Jing Jiang
    CML
ArXiv (abs)PDFHTML

Papers citing "Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge"

4 / 4 papers shown
Title
CausalML: Python Package for Causal Machine Learning
CausalML: Python Package for Causal Machine Learning
Huigang Chen
Totte Harinen
Jeong-Yoon Lee
Mike Yung
Zhenyu Zhao
CML
58
114
0
25 Feb 2020
Causal Effect Inference with Deep Latent-Variable Models
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos
Uri Shalit
Joris Mooij
David Sontag
R. Zemel
Max Welling
CMLBDL
225
749
0
24 May 2017
Approximate Residual Balancing: De-Biased Inference of Average Treatment
  Effects in High Dimensions
Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions
Susan Athey
Guido Imbens
Stefan Wager
CML
479
388
0
25 Apr 2016
Domain Generalization via Invariant Feature Representation
Domain Generalization via Invariant Feature Representation
Krikamol Muandet
David Balduzzi
Bernhard Schölkopf
OOD
147
1,188
0
10 Jan 2013
1