mlsanityData to 7 Oct 2026

Bounds on Causal Effects and Application to High Dimensional Data

arXiv 2106.12121 ↗First posted 23 Jun 2021stat.ME cs.AIcited by 22

Not on the map. Why?

Abstract (arXiv)

This paper addresses the problem of estimating causal effects when adjustment variables in the back-door or front-door criterion are partially observed. For such scenarios, we derive bounds on the causal effects by solving two non-linear optimization problems, and demonstrate that the bounds are sufficient. Using this optimization method, we propose a framework for dimensionality reduction that allows one to trade bias for estimation power, and demonstrate its performance using simulation studies.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 1 of its 25 references that are in the map. First posted on arXiv 23 Jun 2021.

Builds on

1 of 25 references.

References · 1

  1. 2013Probabilities of Causation: Bounds and Identificationcited by 89

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 8; 2023: 8; 2024: 1; 2025: 2; 2026: 2.

22 papers.

Sort:

  1. 2023Counterfactual Identifiability of Bijective Causal Modelscited by 42
  2. 2021An Automated Approach to Causal Inference in Discrete Settingscited by 39
  3. 2022Probabilities of Causation with Nonbinary Treatment and Effectcited by 24
  4. 2023Rethinking Domain Generalization: Discriminability and Generalizabilitycited by 16
  5. 2023Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Modelcited by 14
  6. 2022Unit Selection with Nonbinary Treatment and Effectcited by 12
  7. 2022Probabilities of Causation: Adequate Size of Experimental and Observational Samplescited by 8
  8. 2023Integrating Earth Observation Data into Causal Inference: Challenges and Opportunitiescited by 8
  9. 2023Towards Bounding Causal Effects under Markov Equivalencecited by 8
  10. 2022Unit Selection: Learning Benefit Function from Finite Population Datacited by 6
  11. 2022Unit Selection: Case Study and Comparison with A/B Test Heuristiccited by 5
  12. 2022Probabilities of Causation: Role of Observational Datacited by 5
10 more
  1. 2022Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africacited by 4
  2. 2023Epsilon-Identifiability of Causal Quantitiescited by 4
  3. 2023Approximate Causal Effect Identification under Weak Confoundingcited by 3
  4. 2022Risk-Averse Multi-Armed Bandits with Unobserved Confounders: A Case Study in Emotion Regulation in Mobile Healthcited by 2
  5. 2024Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiencycited by 2
  6. 2025Identification of Probabilities of Causation: from Recursive to Closed-Form Boundscited by 1
  7. 2023Causality-Based Feature Importance Quantifying Methods: PN-FI, PS-FI and PNS-FIcited by 0
  8. 2025A Computational Theory for Efficient Mini Agent Evaluation with Causal Guaranteescited by 0
  9. 2026Uncertainty-aware Causal Decision Making via Effect Bound Decompositioncited by 0
  10. 2026Bounding Probabilities of Causation with Partial Causal Diagramscited by 0