mlsanityData to 13 Oct 2026

Enhanced Route Planning with Calibrated Uncertainty Set

arXiv 2503.10088 ↗First posted 13 Mar 2025cs.LG stat.MLcited by 5

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Abstract (arXiv)

This paper investigates the application of probabilistic prediction methodologies in route planning within a road network context. Specifically, we introduce the Conformalized Quantile Regression for Graph Autoencoders (CQR-GAE), which leverages the conformal prediction technique to offer a coverage guarantee, thus improving the reliability and robustness of our predictions. By incorporating uncertainty sets derived from CQR-GAE, we substantially improve the decision-making process in route planning under a robust optimization framework. We demonstrate the effectiveness of our approach by applying the CQR-GAE model to a real-world traffic scenario. The results indicate that our model significantly outperforms baseline methods, offering a promising avenue for advancing intelligent transportation systems.

Key facts. Cited by 5 papers in the map (data through 13 Oct 2026). Builds on 33 of its 58 references that are in the map. First posted on arXiv 13 Mar 2025.

Builds on

33 of 58 references.

References · 33

  1. 2016Variational Graph Auto-Encoderscited by 1,379
  2. 2019Conformalized Quantile Regressioncited by 625
  3. 2019Conformal Prediction Under Covariate Shiftcited by 513
  4. 2021Adaptive Conformal Inference Under Distribution Shiftcited by 367
  5. 2022Conformal prediction beyond exchangeabilitycited by 351
  6. 2021Graph Neural Network for Traffic Forecasting: A Surveycited by 260
  7. 2018Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecastingcited by 146
  8. 2021ETA Prediction with Graph Neural Networks in Google Mapscited by 130
  9. 2013Data-Driven Robust Optimizationcited by 85
  10. 2023A Survey of Contextual Optimization Methods for Decision Making under Uncertaintycited by 82
  11. 2023Uncertainty Quantification over Graph with Conformalized Graph Neural Networkscited by 79
  12. 2018NeVAE: A Deep Generative Model for Molecular Graphscited by 67
21 more
  1. 2019Machine Learning for Precipitation Nowcasting from Radar Imagescited by 56
  2. 2021Variational Graph Normalized Auto-Encoderscited by 29
  3. 2022Distribution Free Prediction Sets for Node Classificationcited by 28
  4. 2023Conformal Contextual Robust Optimizationcited by 25
  5. 2022Directed Graph Auto-Encoderscited by 22
  6. 2024Trustworthy Classification through Rank-Based Conformal Prediction Setscited by 20
  7. 2021Anomalous Edge Detection in Edge Exchangeable Social Network Modelscited by 17
  8. 2023Predict-then-Calibrate: A New Perspective of Robust Contextual LPcited by 17
  9. 2024Conformal Load Prediction with Transductive Graph Autoencoderscited by 11
  10. 2024Weighted Aggregation of Conformity Scores for Classificationcited by 11
  11. 2024Conformal Thresholded Intervals for Efficient Regressioncited by 11
  12. 2024Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imagingcited by 10
  13. 2022Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti's Theorem for Markov Chainscited by 8
  14. 2023On training locally adaptive CPcited by 8
  15. 2024Entropy Reweighted Conformal Classificationcited by 8
  16. 2024Conformalized Interval Arithmetic with Symmetric Calibrationcited by 8
  17. 2018Algorithms and Uncertainty Sets for Data-Driven Robust Shortest Path Problemscited by 6
  18. 2025Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Trainingcited by 6
  19. 2025Volume-Sorted Prediction Set: Efficient Conformal Prediction for Multi-Target Regressioncited by 6
  20. 2020Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Predictioncited by 5
  21. 2024Adaptive Conformal Inference by Particle Filtering under Hidden Markov Modelscited by 4

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.

  1. 2025Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliabilitycited by 6
  2. 2025Conditional Conformal Risk Adaptationcited by 5
  3. 2026Fast Conformal Prediction using Conditional Interquantile Intervalscited by 4
  4. 2025Residual Reweighted Conformal Prediction for Graph Neural Networkscited by 2
  5. 2026Transit Network Design with Two-Level Demand Uncertainties: A Machine Learning and Contextual Stochastic Optimization Frameworkcited by 0