mlsanityData to 14 Oct 2026

Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data

arXiv 2106.02881 ↗First posted 5 Jun 2021cs.LGcited by 42

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Abstract (arXiv)

Treatment effect estimation from observational data is a critical research topic across many domains. The foremost challenge in treatment effect estimation is how to capture hidden confounders. Recently, the growing availability of networked observational data offers a new opportunity to deal with the issue of hidden confounders. Unlike networked data in traditional graph learning tasks, such as node classification and link detection, the networked data under the causal inference problem has its particularity, i.e., imbalanced network structure. In this paper, we propose a Graph Infomax Adversarial Learning (GIAL) model for treatment effect estimation, which makes full use of the network structure to capture more information by recognizing the imbalance in network structure. We evaluate the performance of our GIAL model on two benchmark datasets, and the results demonstrate superiority over the state-of-the-art methods.

Key facts. Cited by 42 papers in the map (data through 14 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 5 Jun 2021.

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14 of 33 references.

References · 14

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  3. 2017Graph Attention Networkscited by 8,923
  4. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
  5. 2018Learning deep representations by mutual information estimation and maximizationcited by 1,273
  6. 2018Deep Graph Infomaxcited by 1,106
  7. 2018MINE: Mutual Information Neural Estimationcited by 683
  8. 2015Estimation and Inference of Heterogeneous Treatment Effects using Random Forestscited by 600
  9. 2017Causal Effect Inference with Deep Latent-Variable Modelscited by 410
  10. 2020A Survey on Causal Inferencecited by 202
  11. 2017Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processescited by 158
  12. 2018The Blessings of Multiple Causescited by 104
2 more
  1. 2019Using Embeddings to Correct for Unobserved Confounding in Networkscited by 31
  2. 2020Matching in Selective and Balanced Representation Space for Treatment Effects Estimationcited by 30

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 6; 2023: 15; 2024: 19; 2025: 1; 2026: 1.

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  1. 2024A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directionscited by 34
  2. 2023Fair Attribute Completion on Graph with Missing Attributescited by 22
  3. 2024A Causal Explainable Guardrails for Large Language Modelscited by 18
  4. 2023GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classificationcited by 17
  5. 2023CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systemscited by 16
  6. 2023Causal Effect Estimation: Recent Advances, Challenges, and Opportunitiescited by 14
  7. 2023Continual Causal Inference with Incremental Observational Datacited by 13
  8. 2022Learning Individual Treatment Effects under Heterogeneous Interference in Networkscited by 12
  9. 2023Generalization bound for estimating causal effects from observational network datacited by 11
  10. 2022Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Datacited by 9
  11. 2023Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Predictioncited by 9
  12. 2024Professional Agents -- Evolving Large Language Models into Autonomous Experts with Human-Level Competenciescited by 9
30 more
  1. 2023Data-Centric Financial Large Language Modelscited by 8
  2. 2023Estimating Treatment Effects Under Heterogeneous Interferencecited by 7
  3. 2022Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trialscited by 6
  4. 2022Hierarchical Capsule Prediction Network for Marketing Campaigns Effectcited by 5
  5. 2022Incorporating Causal Analysis into Diversified and Logical Response Generationcited by 4
  6. 2024Graph Machine Learning based Doubly Robust Estimator for Network Causal Effectscited by 4
  7. 2024Uplift Modeling Under Limited Supervisioncited by 3
  8. 2024Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variablescited by 3
  9. 2023Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identificationcited by 2
  10. 2024Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimatorscited by 2
  11. 2024Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Datacited by 2
  12. 2022Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Informationcited by 1
  13. 2024Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networkscited by 1
  14. 2023Continual Causal Effect Estimation: Challenges and Opportunitiescited by 0
  15. 2023Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inferencecited by 0
  16. 2023Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adaptercited by 0
  17. 2023GMTR: Graph Matching Transformerscited by 0
  18. 2023DarkShot: Lighting Dark Images with Low-Compute and High-Qualitycited by 0
  19. 2024TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processingcited by 0
  20. 2024TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networkscited by 0
  21. 2024T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Imagecited by 0
  22. 2024Towards Real-world Debiasing: Rethinking Evaluation, Challenge, and Solutioncited by 0
  23. 2024Causal Interventional Prediction System for Robust and Explainable Effect Forecastingcited by 0
  24. 2024IntOPE: Off-Policy Evaluation in the Presence of Interferencecited by 0
  25. 2024Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithmscited by 0
  26. 2024Towards General Deepfake Detection with Dynamic Curriculumcited by 0
  27. 2024Attr-Int: A Simple and Effective Entity Alignment Framework for Heterogeneous Knowledge Graphscited by 0
  28. 2024Disentangled Graph Autoencoder for Treatment Effect Estimationcited by 0
  29. 2025Mask6D: Masked Pose Priors For 6D Object Pose Estimationcited by 0
  30. 2026Treatment Effect Estimation with Differentiated Networked Effect on Graph Datacited by 0