mlsanityData to 14 Oct 2026

Conformal link prediction for false discovery rate control

arXiv 2306.14693 ↗First posted 26 Jun 2023stat.ME stat.MLcited by 9

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Abstract (arXiv)

Most link prediction methods return estimates of the connection probability of missing edges in a graph. Such output can be used to rank the missing edges from most to least likely to be a true edge, but does not directly provide a classification into true and non-existent. In this work, we consider the problem of identifying a set of true edges with a control of the false discovery rate (FDR). We propose a novel method based on high-level ideas from the literature on conformal inference. The graph structure induces intricate dependence in the data, which we carefully take into account, as this makes the setup different from the usual setup in conformal inference, where data exchangeability is assumed. The FDR control is empirically demonstrated for both simulated and real data.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 34 of its 63 references that are in the map. First posted on arXiv 26 Jun 2023.

Builds on

34 of 63 references.

References · 34

  1. 2018How Powerful are Graph Neural Networks?cited by 4,393
  2. 2016Variational Graph Auto-Encoderscited by 1,382
  3. 2017Selective Classification for Deep Neural Networkscited by 852
  4. 2018Link Prediction Based on Graph Neural Networkscited by 832
  5. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  6. 2019Conformalized Quantile Regressioncited by 629
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  9. 2016Least Ambiguous Set-Valued Classifiers with Bounded Error Levelscited by 272
  10. 2021Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcited by 271
  11. 2021Testing for Outliers with Conformal p-valuescited by 134
  12. 2014Controlling the false discovery rate via knockoffscited by 97
22 more
  1. 2023Uncertainty Quantification over Graph with Conformalized Graph Neural Networkscited by 79
  2. 2022Selection by Prediction with Conformal p-valuescited by 69
  3. 2021A statistical framework for efficient out of distribution detection in deep neural networkscited by 28
  4. 2023Conformal Prediction with Missing Valuescited by 25
  5. 2018Imputation and low-rank estimation with Missing Not At Random datacited by 21
  6. 2020A Two-Sample Conditional Distribution Test Using Conformal Prediction and Weighted Rank Sumcited by 19
  7. 2022Integrative conformal p-values for powerful out-of-distribution testing with labeled outlierscited by 19
  8. 2021Anomalous Edge Detection in Edge Exchangeable Social Network Modelscited by 17
  9. 2022Adaptive novelty detection with false discovery rate guaranteecited by 15
  10. 2023Conformal Prediction for Network-Assisted Regressioncited by 14
  11. 2023Conformalized matrix completioncited by 13
  12. 2015Optimal Estimation and Completion of Matrices with Biclustering Structurescited by 12
  13. 2013Link prediction for partially observed networkscited by 7
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  15. 2017Variational Inference for Stochastic Block Models from Sampled Datacited by 7
  16. 2021Semi-supervised multiple testingcited by 7
  17. 2021A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classificationcited by 6
  18. 2017A Power and Prediction Analysis for Knockoffs with Lasso Statisticscited by 5
  19. 2023Distribution-Free Matrix Prediction Under Arbitrary Missing Patterncited by 5
  20. 2018Link prediction for egocentrically sampled networkscited by 4
  21. 2019Graphon Estimation from Partially Observed Network Datacited by 3
  22. 2021BONuS: Multiple multivariate testing with a data-adaptivetest statisticcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 3; 2026: 1.

9 papers.

  1. 2024Conformal Prediction: A Data Perspectivecited by 25
  2. 2024Trustworthy Classification through Rank-Based Conformal Prediction Setscited by 20
  3. 2024Conformal confidence sets for biomedical image segmentationcited by 6
  4. 2025Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Trainingcited by 6
  5. 2025Volume-Sorted Prediction Set: Efficient Conformal Prediction for Multi-Target Regressioncited by 6
  6. 2024Uncertainty Quantification on Graph Learning: A Surveycited by 4
  7. 2025Extending Prediction-Powered Inference through Conformal Predictioncited by 2
  8. 2024Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphscited by 1
  9. 2026GRAPHLCP: Structure-Aware Localized Conformal Prediction on Graphscited by 0