mlsanityData to 14 Oct 2026

β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap

arXiv 2110.05225 ↗First posted 11 Oct 2021stat.ML cs.LG econ.EMcited by 8

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Abstract (arXiv)

As an important problem in causal inference, we discuss the identification and estimation of treatment effects (TEs) under limited overlap; that is, when subjects with certain features belong to a single treatment group. We use a latent variable to model a prognostic score which is widely used in biostatistics and sufficient for TEs; i.e., we build a generative prognostic model. We prove that the latent variable recovers a prognostic score, and the model identifies individualized treatment effects. The model is then learned as β-Intact-VAE--a new type of variational autoencoder (VAE). We derive the TE error bounds that enable representations balanced for treatment groups conditioned on individualized features. The proposed method is compared with recent methods using (semi-)synthetic datasets.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 30 of its 85 references that are in the map. First posted on arXiv 11 Oct 2021.

Builds on

30 of 85 references.

References · 30

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18 more
  1. 2020An Introduction to Proximal Causal Learningcited by 95
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  16. 2021Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlapcited by 9
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  18. 2019Posterior Average Effectscited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 2; 2026: 2.

8 papers.

  1. 2023In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimationcited by 29
  2. 2023Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Modelcited by 14
  3. 2024Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Modelscited by 10
  4. 2024Causal Inference with Latent Variables: Recent Advances and Future Prospectivescited by 4
  5. 2025Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learningcited by 3
  6. 2025ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencodercited by 1
  7. 2026Cross-Domain Off-Policy Evaluation and Learning for Contextual Banditscited by 0
  8. 2026Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimationcited by 0