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Learning Individual Causal Effects from Networked Observational Data

Learning Individual Causal Effects from Networked Observational Data

8 June 2019
Ruocheng Guo
Wenlin Yao
Huan Liu
    CML
    OOD
ArXivPDFHTML

Papers citing "Learning Individual Causal Effects from Networked Observational Data"

19 / 19 papers shown
Title
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang
Shuhan Liu
Song Wang
Weili Shi
Chen Chen
Pan Li
Sheng Li
Jundong Li
Kaize Ding
OOD
53
2
0
25 Oct 2024
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal
  Inference in Networks
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks
Xiaojing Du
Feiyu Yang
Wentao Gao
Xiongren Chen
CML
37
1
0
13 Sep 2024
Conformal Counterfactual Inference under Hidden Confounding
Conformal Counterfactual Inference under Hidden Confounding
Zonghao Chen
Ruocheng Guo
Jean-François Ton
Yang Liu
CML
OffRL
50
2
0
20 May 2024
Doubly Robust Causal Effect Estimation under Networked Interference via
  Targeted Learning
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
Weilin Chen
Ruichu Cai
Zeqin Yang
Jie Qiao
Yuguang Yan
Zijian Li
Zhifeng Hao
CML
44
7
0
06 May 2024
Graph Neural Network with Two Uplift Estimators for Label-Scarcity
  Individual Uplift Modeling
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling
Dingyuan Zhu
Daixin Wang
Qing Cui
Kun Kuang
Yan Zhang
Yulin Kang
Jun Zhou
40
3
0
11 Mar 2024
A Look into Causal Effects under Entangled Treatment in Graphs:
  Investigating the Impact of Contact on MRSA Infection
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection
Jing Ma
Chen Chen
A. Vullikanti
Ritwick Mishra
Gregory R. Madden
Daniel Borrajo
Jundong Li
CML
33
4
0
17 Jul 2023
A Comprehensive Survey on Deep Graph Representation Learning
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju
Zheng Fang
Yiyang Gu
Zequn Liu
Qingqing Long
...
Jingyang Yuan
Yusheng Zhao
Yifan Wang
Xiao Luo
Ming Zhang
GNN
AI4TS
54
141
0
11 Apr 2023
Continual Causal Inference with Incremental Observational Data
Continual Causal Inference with Incremental Observational Data
Zhixuan Chu
Ruopeng Li
S. Rathbun
Sheng Li
CML
43
14
0
03 Mar 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders
Estimating Treatment Effects in Continuous Time with Hidden Confounders
Defu Cao
James Enouen
Yong-Jin Liu
CML
35
2
0
19 Feb 2023
Interpreting Unfairness in Graph Neural Networks via Training Node
  Attribution
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution
Yushun Dong
Song Wang
Jing Ma
Ninghao Liu
Jundong Li
44
21
0
25 Nov 2022
Learning Individual Treatment Effects under Heterogeneous Interference
  in Networks
Learning Individual Treatment Effects under Heterogeneous Interference in Networks
Ziyu Zhao
Yuqi Bai
Kun Kuang
Ruoxuan Xiong
Fei Wu
CML
24
6
0
25 Oct 2022
Learning Causal Effects on Hypergraphs
Learning Causal Effects on Hypergraphs
Jing Ma
Mengting Wan
Longqi Yang
Jundong Li
Brent J. Hecht
J. Teevan
CML
27
48
0
07 Jul 2022
A Causal Research Pipeline and Tutorial for Psychologists and Social
  Scientists
A Causal Research Pipeline and Tutorial for Psychologists and Social Scientists
M. Vowels
CML
32
2
0
10 Jun 2022
Estimating Social Influence from Observational Data
Estimating Social Influence from Observational Data
Dhanya Sridhar
Caterina De Bacco
David M. Blei
32
3
0
24 Mar 2022
Evaluation Methods and Measures for Causal Learning Algorithms
Evaluation Methods and Measures for Causal Learning Algorithms
Lu Cheng
Ruocheng Guo
Raha Moraffah
Paras Sheth
K. S. Candan
Huan Liu
CML
ELM
24
51
0
07 Feb 2022
Heterogeneous Peer Effects in the Linear Threshold Model
Heterogeneous Peer Effects in the Linear Threshold Model
Christopher Tran
Elena Zheleva
14
10
0
27 Jan 2022
Counterfactual Evaluation of Treatment Assignment Functions with
  Networked Observational Data
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
Ruocheng Guo
Jundong Li
Huan Liu
CML
OffRL
33
21
0
22 Dec 2019
A Survey of Learning Causality with Data: Problems and Methods
A Survey of Learning Causality with Data: Problems and Methods
Ruocheng Guo
Lu Cheng
Jundong Li
P. R. Hahn
Huan Liu
CML
32
168
0
25 Sep 2018
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
232
719
0
12 May 2016
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