Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals | Paper Citation Record

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This paper cites Approximating score-based explanation techniques using conformal regression.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Approximating score-based explanation techniques using conformal regression

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This paper cites Estimating quality of approximated shapley values using conformal prediction.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Estimating quality of approximated shapley values using conformal prediction

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This paper cites Getting a {clue}: A method for explaining uncertainty estimates.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Getting a {clue}: A method for explaining uncertainty estimates

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This paper cites Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI.Information Fusion, 58:82–115, June 2020.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI.Information Fusion, 58:82–115, June 2020

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This paper cites Explainingpredictive uncertainty by exposing second-order effects.Pattern Recognition, 160:111171, 2025.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Explainingpredictive uncertainty by exposing second-order effects.Pattern Recognition, 160:111171, 2025

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This paper cites Blogfeedback.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Blogfeedback

Reference 7

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This paper cites The proportional Shapley value and applications.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals The proportional Shapley value and applications

Reference 8

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This paper cites RKHS-SHAP: Shapley Values for Kernel Methods.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals RKHS-SHAP: Shapley Values for Kernel Methods

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This paper cites Learning to explain: An information-theoretic perspective on model interpretation.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Learning to explain: An information-theoretic perspective on model interpretation

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This paper cites Fair prediction with disparate impact: A study of bias in recidivism prediction instruments.Big Data, 5(2):153–163, 2017.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Fair prediction with disparate impact: A study of bias in recidivism prediction instruments.Big Data, 5(2):153–163, 2017

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This paper cites Understanding global feature contributions with additive importance measures.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Understanding global feature contributions with additive importance measures

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This paper cites Explaining by removing: A unified framework for model explanation.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Explaining by removing: A unified framework for model explanation

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This paper cites Kernel-based ANOVA decomposition and Shapley effects -- Application to global sensitivity analysis.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Kernel-based ANOVA decomposition and Shapley effects -- Application to global sensitivity analysis

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This paper cites On Harsanyi Dividends and Asymmetric Values.International Game Theory Review, 19(03):1750012, September 2017.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals On Harsanyi Dividends and Asymmetric Values.International Game Theory Review, 19(03):1750012, September 2017

Reference 15

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This paper cites A new proof for Weber’s characterization of the random order values.Mathematical Social Sciences, 49(3):327–334, May 2005.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals A new proof for Weber’s characterization of the random order values.Mathematical Social Sciences, 49(3):327–334, May 2005

Reference 16

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This paper cites On harsanyi payoff vectors and the weber set.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals On harsanyi payoff vectors and the weber set

Reference 17

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This paper cites Bike sharing.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Bike sharing

Reference 18

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This paper cites Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis

Reference 19

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Friedman

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This paper cites Identifying homogeneous and interpretable groups for conformai prediction.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Identifying homogeneous and interpretable groups for conformai prediction

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This paper cites Harsanyi.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Harsanyi

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This paper cites Proportional marginal effects for global sensitivity analysis.SIAM/ASA Journal on Uncertainty Quantification, 12(2): 667–692, 2024.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Proportional marginal effects for global sensitivity analysis.SIAM/ASA Journal on Uncertainty Quantification, 12(2): 667–692, 2024

Reference 23

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This paper cites Causal shapley values: exploiting causal knowledge to explain individual predictions of complex models.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Causal shapley values: exploiting causal knowledge to explain individual predictions of complex models

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This paper cites Quantile-constrained wasserstein projections for robust interpretability of numerical and machine learning models.Electronic Journal of Statistics, 18(2):2721 – 2770, 2024.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Quantile-constrained wasserstein projections for robust interpretability of numerical and machine learning models.Electronic Journal of Statistics, 18(2):2721 – 2770, 2024

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This paper cites A Review on Global Sensitivity Analysis Methods.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals A Review on Global Sensitivity Analysis Methods

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Different Views of Interpretability

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Identifying Drivers of Predictive Aleatoric Uncertainty

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Shapley-value based inductive conformal prediction

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Fast- SHAP: Real-time shapley value estimation

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Don’t be fooled: label leakage in explanation methods and the importance of their quantitative evaluation

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Interpretable and specialized conformal predictors

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Customized interpretable conformal regressors

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This paper cites Navigating the maze of explainable ai: A systematic approach to evaluating methods and metrics.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Navigating the maze of explainable ai: A systematic approach to evaluating methods and metrics

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Tibshirani, and Larry Wasserman

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This paper cites Diverse, global and amortised counterfactual explana- tions for uncertainty estimates.Proceedings of the AAAI Conference on Artificial Intelligence, 36: 7390–7398, 06 2022.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Diverse, global and amortised counterfactual explana- tions for uncertainty estimates.Proceedings of the AAAI Conference on Artificial Intelligence, 36: 7390–7398, 06 2022

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals High Dimensional Model Representations

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Calibrated explanations: With uncertainty information and counterfactuals.Expert Syst

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Calibrated explanations for multi-class

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals A unified approach to interpreting model predictions

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Lundberg, Gabriel Erion, Hugh Chen, Alex DeGrave, Jordan M

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Integrating permutation feature importance with conformal prediction for robust explainable artificial intelligence in predictive process mon- itoring

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Dean, and Thomas J

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals shapiq: Shapley interactions for machine learning

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Confiderai: Conformal interpretable-by-design score function for explainable and reliable artificial intelligence

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Osborne and Ariel Rubinstein.A course in game theory

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Unresolved cited work

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Ensuring Medical AI Safety: Interpretability-Driven Detection and Mitigation of Spurious Model Behavior and Associated Data

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Attribution of predictive uncertainties in classification models

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Aliş, Jeffrey Shorter, and Kyurhee Shim

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Physicochemical properties of protein tertiary structure

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Communities and crime

Reference 54

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This paper cites Robert and George Casella.Monte Carlo Statistical Methods (Springer Texts in Statistics).

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Robert and George Casella.Monte Carlo Statistical Methods (Springer Texts in Statistics)

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.867774Z

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This paper cites Conformalized Quantile Regres- sion.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Conformalized Quantile Regres- sion

Reference 56

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Observation 7e01735c-24d0-49d6-bdc2-a70f98d7e353 · outbound

This paper cites On the foundations of combinatorial theory I.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals On the foundations of combinatorial theory I

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Resolution: unresolved; no resolver link, observed 2026-08-15T20:27:39.882155Z

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This paper cites A tutorial on conformal prediction.J.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals A tutorial on conformal prediction.J

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.854024Z

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Observation 8a9bad05-9c78-4172-ae4c-5e29fbee5a4b · outbound

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Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:27:40.846403Z

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Shapley.17

Reference 60

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Robinson

Reference 61

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Observation 745ab72a-6993-462f-863b-ac27b52acc0a · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Facebook comment volume

Reference 62

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This paper cites Sobol’ and Yu.L.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Sobol’ and Yu.L

Reference 63

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This paper cites Nelson, and Jeremy Staum.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Nelson, and Jeremy Staum

Reference 64

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals An efficient explanation of individual classifications using game theory.Journal of Machine Learning Research, 11(1):1–18, 2010

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.832028Z

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals The Many Shapley Values for Model Explanation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.825293Z

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Observation 88e9f7dc-89d6-401e-af6d-c09f176b6ead · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Virtual library of simulation experiments: Test functions and datasets

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.818817Z

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Observation 5e09907e-06aa-4fb4-9a2c-5bcc0e30545c · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals The Harsanyi Set for Cooperative TU-Games

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.811946Z

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This paper cites Algorithmic Learning in a Ran- dom World.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Algorithmic Learning in a Ran- dom World

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Optimization-based uncertainty attribution via learning informative perturbations

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Explaining predictive uncertainty with information theoretic shapley values

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.804898Z

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Observation 8b31e80f-f882-4137-9ab1-36911a7c7f36 · outbound

This paper cites Cambridge University Press, 1988.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Cambridge University Press, 1988

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.797180Z

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Observation be1da21b-7d3f-4c07-860c-25fd1cb4bebe · outbound

This paper cites Boosted conformal prediction intervals.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Boosted conformal prediction intervals

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.790014Z

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Observation 37cccfde-2099-4236-9bb9-796761609d5a · outbound

This paper cites Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals ConformaSight: Conformal prediction-based global and model-agnostic explainability framework

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.782359Z

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Observation 080acd5e-91d5-4792-8b3d-76255b529c68 · outbound

This paper cites Concrete compressive strength.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Concrete compressive strength

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T20:27:39.937006Z

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Observation 50a1b971-5bd4-4bd3-8e9d-9c2ed010bfb8 · outbound

This paper cites Post-hoc predictive uncertainty quantification: methods with applications to electricity price forecasting.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals Post-hoc predictive uncertainty quantification: methods with applications to electricity price forecasting

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.775251Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 22e099be-e220-4c21-830a-c010233b5577 · outbound

This paper cites model explanations.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals model explanations

Reference 78

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals ISBN 978-1-4899-7546-1 978-1-4899-7547-8

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Resolution: verified exact; doi, observed 2026-08-15T20:27:40.064342Z

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Observation ed1079a6-a891-41e9-b483-c3f192b4bbbb · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals URLhttps://proceedings.mlr.press/v230/alkhatib24a.html

Reference 174

Resolution: unresolved; no resolver link, observed 2026-08-15T20:27:39.713138Z

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Reference 1994

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:27:40.883368Z

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals doi: https://doi.org/10.1016/S0010-4655(98)00156-8

Reference 1999

Resolution: verified exact; doi, observed 2026-08-15T20:27:39.996498Z

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Observation d13fddc9-2e3d-4207-8097-2e488b151133 · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals ISBN 978-3-031-63800-8

Reference 2024

Resolution: verified exact; doi, observed 2026-08-15T20:27:39.973794Z

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Observation 52f2860e-cf27-4992-bdf6-450e4eac40b0 · outbound

This paper cites URL https://www.sciencedirect.

Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals URL https://www.sciencedirect

Reference 3203

Resolution: unresolved; no resolver link, observed 2026-08-15T20:27:39.726894Z

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals URL https://doi.org/10.1016/j.eswa.2024.123154

Reference 4174

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Observation 06f48dc4-9cee-4b54-9ca7-b4f9ca28c56e · outbound

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Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals URLhttps://proceedings.mlr.press/v206/jethani23a.html

Reference 8953

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:27:40.949813Z

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