Inductive Confidence Machines for Regression

The Nature of Statistical Learning Theory

Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138 · see citing works

Statistical Learning Theory

Wu, Y., & Vapnik, V. N. (1999) · Technometrics · doi:10.2307/1271368 · Cited by 27,236 · see citing works

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

Cristianini, N., & Shawe-Taylor, J. (2000) · doi:10.1017/cbo9780511801389 · Cited by 13,855 · see citing works

An Introduction to Kolmogorov Complexity and Its Applications

Li, M., & Vitanyi, P. M. B. (2019) · Texts in computer science · doi:10.1007/978-3-030-11298-1 · Cited by 3,752 · see citing works

Statistical learning theory

Vapnik, V. N. 1. (1998) · Cited by 2,163 · see citing works

An Introduction to Kolmogorov Complexity and Its Applications

Li, M., & Vitanyi, P. M. B. (1997) · Springer eBooks · doi:10.1007/978-1-4757-2606-0 · Cited by 1,792 · see citing works

Nonparametric methods in statistics.

Fraser, D. A. S. (1956) · John Wiley & Sons, Inc. eBooks · doi:10.1037/13191-000 · Cited by 413 · see citing works

Learning by TransductionPreprint

Gammerman, A., Vovk, V., & Vapnik, V. N. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.7375 · Cited by 330 · see citing works

Nonparametric Methods in Statistics.

Brixey, J. C., & Fraser, D. A. S. (1957) · American Mathematical Monthly · doi:10.2307/2309988 · Cited by 246 · see citing works

Machine-Learning Applications of Algorithmic Randomness

Vovk, V., Gammerman, A., & Saunders, C. J. (1999) · ePrints Soton (University of Southampton) · Cited by 153 · see citing works

Transduction with Confidence and Credibility

Saunders, C. J., Gammerman, A., & Vovk, V. (1999) · ePrints Soton (University of Southampton) · Cited by 151 · see citing works

Transductive Confidence Machines for Pattern Recognition

Proedrou, K., Nouretdinov, I., Vovk, V., & Gammerman, A. (2002) · Lecture notes in computer science · doi:10.1007/3-540-36755-1_32 · Cited by 147 · see citing works

Comparing the Bayes and Typicalness Frameworks

Melluish, T., Saunders, C. J., Nouretdinov, I., & Vovk, V. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44795-4_31 · Cited by 79 · see citing works

Ridge Regression Confidence Machine

Nouretdinov, I., Melluish, T., & Vovk, V. (2001) · Cited by 72 · see citing works

Prediction algorithms and confidence measures based on algorithmic randomness theory

Gammerman, A., & Vovk, V. (2002) · Theoretical Computer Science · doi:10.1016/s0304-3975(02)00100-7 · Cited by 60 · see citing works

Non-Parametric Methods in Statistics.

Stuart, A., & Fraser, D. A. S. (1958) · Biometrika · doi:10.2307/2333218 · Cited by 44 · see citing works

Computationally Efficient Transductive Machines

Saunders, C. J., Gammerman, A., & Vovk, V. (2000) · Lecture notes in computer science · doi:10.1007/3-540-40992-0_25 · Cited by 28 · see citing works

Transductive Confidence Machine Is Universal

Nouretdinov, I., V'yugin, V. V., & Gammerman, A. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-39624-6_23 · Cited by 11 · see citing works

Distribution-Free Predictive Inference for Regression

Lei, J., G’Sell, M., Rinaldo, A., Tibshirani, R. J., & Wasserman, L. (2018) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1307116 · Cited by 1,049 · see citing works

Conformalized Quantile Regression

Romano, Y., Patterson, E., & Candès, E. J. (2019) · arXiv · doi:10.48550/arxiv.1905.03222 · Cited by 236 · see citing works

Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination

Norinder, U., Carlsson, L., Boyer, S. K., & Eklund, M. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci5001168 · Cited by 208 · see citing works

Conformal prediction: A unified review of theory and new challenges

Fontana, M., Zeni, G., & Vantini, S. (2022) · Bernoulli · doi:10.3150/21-bej1447 · Cited by 207 · see citing works

GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning

Esposito, C., Landrum, G. A., Schneider, N., Stiefl, N., & Riniker, S. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c00160 · Cited by 203 · see citing works

Inductive Conformal Prediction: Theory and Application to Neural Networks

Papadopoulos, H. (2008) · InTech eBooks · doi:10.5772/6078 · Cited by 195 · see citing works

Regression conformal prediction with random forests

Johansson, U., Boström, H., Löfström, T., & Linusson, H. (2014) · Machine Learning · doi:10.1007/s10994-014-5453-0 · Cited by 185 · see citing works

Least Ambiguous Set-Valued Classifiers With Bounded Error Levels

Sadinle, M., Lei, J., & Wasserman, L. (2017) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1395341 · Cited by 181 · see citing works

The limits of distribution-free conditional predictive inference

Barber, R. F., Candès, E. J., Ramdas, A., & Tibshirani, R. J. (2020) · Information and Inference A Journal of the IMA · doi:10.1093/imaiai/iaaa017 · Cited by 163 · see citing works

Regression Conformal Prediction with Nearest Neighbours

Papadopoulos, H., Vovk, V., & Gammerman, A. (2011) · Journal of Artificial Intelligence Research · doi:10.1613/jair.3198 · Cited by 161 · see citing works

Conformal Prediction for Reliable Machine Learning: Theory, Adaptations and Applications

Balasubramanian, V. N., Ho, S.-S., & Vovk, V. (2014) · Cited by 155 · see citing works

Transductive Confidence Machines for Pattern Recognition

Proedrou, K., Nouretdinov, I., Vovk, V., & Gammerman, A. (2002) · Lecture notes in computer science · doi:10.1007/3-540-36755-1_32 · Cited by 147 · see citing works

Conformal Prediction Under Covariate ShiftPreprint

Tibshirani, R. J., Barber, R. F., Candès, E. J., & Ramdas, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.06019 · Cited by 146 · see citing works

Distribution-free, Risk-controlling Prediction Sets

Bates, S., Angelopoulos, A., Lei, L., Malik, J., & Jordan, M. (2021) · Journal of the ACM · doi:10.1145/3478535 · Cited by 144 · see citing works

Hedging Predictions in Machine Learning

Gammerman, A., & Vovk, V. (2007) · The Computer Journal · doi:10.1093/comjnl/bxl065 · Cited by 135 · see citing works

Conditional validity of inductive conformal predictors

Vovk, V. (2013) · Machine Learning · doi:10.1007/s10994-013-5355-6 · Cited by 225 · see citing works

A Self-Interpretable Soft Sensor Based on Deep Learning and Multiple Attention Mechanism: From Data Selection to Sensor Modeling

Guo, R., Liu, H., Xie, G., Zhang, Y. M., & Liu, D. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3181692 · Cited by 118 · see citing works

A Martingale Framework for Detecting Changes in Data Streams by Testing Exchangeability

Ho, S.-S., & Wechsler, H. L. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.48 · Cited by 115 · see citing works

Adaptive Conformal Inference Under Distribution ShiftPreprint

Gibbs, I., & Candès, E. J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.00170 · Cited by 114 · see citing works

Testing for outliers with conformal p-values

Bates, S., Candès, E. J., Lei, L., Romano, Y., & Sesia, M. (2023) · The Annals of Statistics · doi:10.1214/22-aos2244 · Cited by 112 · see citing works

Reliable prediction intervals with regression neural networks

Papadopoulos, H., & Haralambous, H. (2011) · Neural Networks · doi:10.1016/j.neunet.2011.05.008 · Cited by 108 · see citing works

Learn then test: Calibrating predictive algorithms to achieve risk control

Angelopoulos, A. N., Bates, S., Candès, E. J., Jordan, M. I., & Lei, L. (2025) · The Annals of Applied Statistics · doi:10.1214/24-aoas1998 · Cited by 100 · see citing works

Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting

Jensen, V., Bianchi, F. M., & Anfinsen, S. N. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3217694 · Cited by 98 · see citing works

Uncertainty Sets for Image Classifiers using Conformal Prediction

Angelopoulos, A., Bates, S., Malik, J., & Jordan, M. I. (2020) · arXiv · doi:10.48550/arxiv.2009.14193 · Cited by 79 · see citing works

A comparison of some conformal quantile regression methods

Sesia, M., & Candès, E. J. (2020) · Stat · doi:10.1002/sta4.261 · Cited by 75 · see citing works

Nested conformal prediction and quantile out-of-bag ensemble methods

Gupta, C., Kuchibhotla, A. K., & Ramdas, A. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108496 · Cited by 72 · see citing works

Localized conformal prediction: a generalized inference framework for conformal prediction

Guan, L. (2022) · Biometrika · doi:10.1093/biomet/asac040 · Cited by 69 · see citing works

Well-calibrated confidence measures for multi-label text classification with a large number of labels

Maltoudoglou, L., Paisios, A., Lenc, L., Martı́nek, J., Král, P., & Papadopoulos, H. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108271 · Cited by 69 · see citing works

Valid prediction intervals for regression problems

Dewolf, N., Bernard De Baets, C., & Waegeman, W. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10178-5 · Cited by 69 · see citing works

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets

Sun, J., Carlsson, L., Ahlberg, E., Norinder, U., Engkvist, O., & Chen, H. (2017) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.7b00159 · Cited by 69 · see citing works

Conformal Prediction with Neural Networks

Papadopoulos, H., Vovk, V., & Gammerman, A. (2007) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai.2007.47 · Cited by 66 · see citing works

Improving the Confidence of Machine Translation Quality Estimates

Specia, L., Turchi, M., Wang, Z., Shawe-Taylor, J. S., & Saunders, C. J. (2009) · Cited by 57 · see citing works

Conformal Prediction: A Data Perspective

Zhou, X., Chen, B., Gui, Y., & Cheng, L. (2025) · ACM Computing Surveys · doi:10.1145/3736575 · Cited by 55 · see citing works

Air traffic controller workload level prediction using conformalized dynamical graph learning

Pang, Y., Hu, J., Lieber, C. S., Cooke, N. J., & Liu, Y. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.102113 · Cited by 53 · see citing works

Machine learning based conformal predictors for uncertainty-aware compressive strength estimation of concrete

Tamuly, P., & Nava, V. (2025) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2025.141844 · Cited by 50 · see citing works

Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector

Fischer-Abaigar, U., Kern, C. A., Barda, N., & Kreuter, F. (2024) · Government Information Quarterly · doi:10.1016/j.giq.2024.101976 · Cited by 49 · see citing works

Conformal matrix factorization based recommender system

Himabindu, T. V. R., Padmanabhan, V., & Pujari, A. K. (2018) · Information Sciences · doi:10.1016/j.ins.2018.04.004 · Cited by 46 · see citing works

With Malice Toward None: Assessing Uncertainty via Equalized Coverage

Romano, Y., Barber, R. F., Sabatti, C., & Candès, E. J. (2020) · Harvard Data Science Review · doi:10.1162/99608f92.03f00592 · Cited by 45 · see citing works

QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping

Škuta, C., Cortés‐Ciriano, I., Dehaen, W., Kříž, P., van Westen, G. J. P., Tetko, I. V., Bender, A., & Svozil, D. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00443-6 · Cited by 44 · see citing works

Improving urban water demand forecast using conformal prediction-based hybrid machine learning models

Iwakin, O. M., & Moazeni, F. K. (2024) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2023.104721 · Cited by 43 · see citing works

Integrating permutation feature importance with conformal prediction for robust Explainable Artificial Intelligence in predictive process monitoring

Mehdiyev, N., Majlatow, M., & Fettke, P. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110363 · Cited by 43 · see citing works

Predictive Inference Is Free with the Jackknife+-after-BootstrapPreprint

Kim, B., Chen, X., & Barber, R. F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.09025 · Cited by 43 · see citing works

Reliable Probability Estimates Based on Support Vector Machines for Large Multiclass Datasets

Lambrou, A., Papadopoulos, H., Nouretdinov, I., & Gammerman, A. (2012) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-33412-2_19 · Cited by 41 · see citing works

The Ramification Problem in Temporal Databases: Concurrent Execution with Conflicting Constraints

Papadakis, N., Antoniou, G., & Plexousakis, D. (2007) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai.2007.77 · Cited by 41 · see citing works

Copula-based conformal prediction for multi-target regression

Messoudi, S., Destercke, S., & Rousseau, S. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108101 · Cited by 39 · see citing works

Reliable diagnosis of acute abdominal pain with conformal prediction

Papadopoulos, H., Gammerman, A., & Vovk, V. (2009) · International journal of engineering intelligent systems for electrical engineering and communications · Cited by 39 · see citing works

Conformal prediction bands for multivariate functional data

Diquigiovanni, J., Fontana, M., & Vantini, S. (2021) · Journal of Multivariate Analysis · doi:10.1016/j.jmva.2021.104879 · Cited by 38 · see citing works

Conformal Risk Control

Angelopoulos, A. N., Bates, S., Fisch, A., Lei, L., & Schuster, T. (2022) · arXiv · doi:10.48550/arxiv.2208.02814 · Cited by 37 · see citing works

Personalized uncertainty quantification in artificial intelligence

Chakraborti, T., Banerji, C. R. S., Marandon, A., Hellon, V., Mitra, R., Lehmann, B., Bräuninger, L., McGough, S. F., Turkay, Ç., Frangi, A. F., et al. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-025-01024-8 · Cited by 37 · see citing works

Guaranteed Coverage Prediction Intervals With Gaussian Process Regression

Papadopoulos, H. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3418214 · Cited by 36 · see citing works

Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images

Wieslander, H., Harrison, P. J., Skogberg, G., Jackson, S. G., Fridén, M., Karlsson, J., Spjuth, O., & Wählby, C. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2996300 · Cited by 36 · see citing works

Accelerating difficulty estimation for conformal regression forests

Boström, H., Linusson, H., Löfström, T., & Johansson, U. (2017) · Annals of Mathematics and Artificial Intelligence · doi:10.1007/s10472-017-9539-9 · Cited by 34 · see citing works

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

Ulmer, D., Hardmeier, C., & Frellsen, J. (2021) · IT University Of Copenhagen (IT University of Copenhagen) · doi:10.48550/arxiv.2110.03051 · Cited by 33 · see citing works

Interpretable regression trees using conformal prediction

Johansson, U., Linusson, H., Löfström, T., & Boström, H. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.12.041 · Cited by 32 · see citing works

Introduction to conformal predictors

Toccaceli, P. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108507 · Cited by 30 · see citing works

A SEVA soft sensor method based on self-calibration model and uncertainty description algorithm

Liu, Y., Daoping, H., & Li, Z. (2013) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2013.04.009 · Cited by 29 · see citing works

Uncertainty Quantification and Interpretability for Clinical Trial Approval Prediction

Lu, Y., Chen, T., Hao, N., Rechem, C. V., Chen, J., & Fu, T. (2024) · Health Data Science · doi:10.34133/hds.0126 · Cited by 28 · see citing works

AI allows pre-screening of FGFR3 mutational status using routine histology slides of muscle-invasive bladder cancer

Bannier, P., Saillard, C., Mann, P., Touzot, M., Maussion, C., Matek, C., Klümper, N., Breyer, J., Wirtz, R. M., Sikic, D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-55331-6 · Cited by 27 · see citing works

Using nondeterministic learners to alert on coffee rust disease

Luaces, O., Rodrigues, L. H. A., Meira, C. A. A., & Bahamonde, A. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.05.003 · Cited by 27 · see citing works

Confidence Predictions for the Diagnosis of Acute Abdominal Pain

Papadopoulos, H., Gammerman, A., & Vovk, V. (2009) · IFIP advances in information and communication technology · doi:10.1007/978-1-4419-0221-4_22 · Cited by 25 · see citing works

Conformalized-DeepONet: A distribution-free framework for uncertainty quantification in deep operator networks

Moya, C., Mollaali, A., Zhang, Z., Lu, L., & Lin, G. (2024) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2024.134418 · Cited by 24 · see citing works

Inductive Venn Prediction

Lambrou, A., Nouretdinov, I., & Papadopoulos, H. (2014) · Annals of Mathematics and Artificial Intelligence · doi:10.1007/s10472-014-9420-z · Cited by 24 · see citing works

Selection and Aggregation of Conformal Prediction Sets

Yang, Y., & Kuchibhotla, A. K. (2024) · Journal of the American Statistical Association · doi:10.1080/01621459.2024.2344700 · Cited by 22 · see citing works

Reliable probabilistic classification with neural networks

Papadopoulos, H. (2012) · Neurocomputing · doi:10.1016/j.neucom.2012.07.034 · Cited by 22 · see citing works

CD-split and HPD-split: efficient conformal regions in high dimensionsPreprint

Izbicki, R., Shimizu, G. Y., & Stern, R. B. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.12778 · Cited by 22 · see citing works

Model-agnostic nonconformity functions for conformal classification

Johansson, U., Linusson, H., Löfström, T., & Boström, H. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7966105 · Cited by 21 · see citing works

Neural Networks Regression Inductive Conformal Predictor and Its Application to Total Electron Content Prediction

Papadopoulos, H., & Haralambous, H. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15819-3_4 · Cited by 21 · see citing works

Probabilistic Reframing for Cost-Sensitive Regression

Hernández‐Orallo, J. (2014) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2641758 · Cited by 21 · see citing works

Enhancing decision support in crop production: Analyzing conformal prediction for uncertainty quantification

Farag, M., Emam, A., Leonhardt, J., & Roscher, R. (2025) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2025.110559 · Cited by 20 · see citing works

Development and Evaluation of Conformal Prediction Methods for Quantitative Structure–Activity Relationship

Xu, Y., Liaw, A. I., Sheridan, R. P., & Svetnik, V. (2024) · ACS Omega · doi:10.1021/acsomega.4c02017 · Cited by 20 · see citing works

Distribution-free binary classification: prediction sets, confidence intervals and calibrationPreprint

Gupta, C., Podkopaev, A., & Ramdas, A. (2020) · Neural Information Processing Systems · doi:10.48550/arxiv.2006.10564 · Cited by 106 · see citing works

Conformal Sensitivity Analysis for Individual Treatment Effects

Yin, M., Shi, C., Wang, Y., & Blei, D. M. (2022) · Journal of the American Statistical Association · doi:10.1080/01621459.2022.2102503 · Cited by 19 · see citing works

Efficient conformal predictor ensembles

Linusson, H., Johansson, U., & Boström, H. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.07.113 · Cited by 19 · see citing works

Rule extraction with guarantees from regression models

Johansson, U., Sönströd, C., Löfström, T., & Boström, H. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108554 · Cited by 19 · see citing works

Assessment of Stroke Risk Based on Morphological Ultrasound Image Analysis with Conformal Prediction

Lambrou, A., Papadopoulos, H., Kyriacou, E. C., Pattichis, C. S., Pattichis, M. S., Gammerman, A., & Nicolaides, A. N. (2010) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-16239-8_21 · Cited by 19 · see citing works

Conformal Semantic Image Segmentation: Post-hoc Quantification of Predictive Uncertainty

Mossina, L., Dalmau, J., & Andéol, L. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00361 · Cited by 18 · see citing works

Improving conformalized quantile regression through cluster-based feature relevance

Sousa, M., Tomé, A. M., & Moreira, J. E. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122322 · Cited by 18 · see citing works

Reliable Probabilistic Prediction for Medical Decision Support

Papadopoulos, H. (2011) · IFIP International Federation for Information Processing/IFIP · doi:10.1007/978-3-642-23960-1_32 · Cited by 18 · see citing works

Responsible machine learning for United States Air Force pilot candidate selection

Wasilefsky, D., Caballero, W. N., Johnstone, C., Gaw, N. B., & Jenkins, P. R. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114198 · Cited by 17 · see citing works

Multi split conformal prediction

Solari, A., & Djordjilović, V. (2022) · Statistics & Probability Letters · doi:10.1016/j.spl.2022.109395 · Cited by 17 · see citing works

Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers

Linusson, H., Johansson, U., Boström, H., & Löfström, T. (2014) · Lecture notes in computer science · doi:10.1007/978-3-662-44722-2_28 · Cited by 17 · see citing works

Reliable prediction intervals with directly optimized inductive conformal regression for deep learning

Lei, H., & Bellotti, A. G. (2023) · Neural Networks · doi:10.1016/j.neunet.2023.09.008 · Cited by 16 · see citing works

Conformal prediction bands for two-dimensional functional time series

Ajroldi, N., Diquigiovanni, J., Fontana, M., & Vantini, S. (2023) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2023.107821 · Cited by 16 · see citing works

Uncertainty quantification for direction-of-arrival estimation with conformal prediction

Khurjekar, I. D., & Gerstoft, P. (2023) · The Journal of the Acoustical Society of America · doi:10.1121/10.0020655 · Cited by 15 · see citing works

Quantifying Deep Learning Model Uncertainty in Conformal Prediction

Karimi, H., & Samavi, R. (2023) · Proceedings of the AAAI Symposium Series · doi:10.1609/aaaiss.v1i1.27492 · Cited by 15 · see citing works

Data Science Methods for Real-World Evidence Generation in Real-World Data

Liu, F. (2024) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-102423-113220 · Cited by 15 · see citing works

EVALUATION OF THE RISK OF STROKE WITH CONFIDENCE PREDICTIONS BASED ON ULTRASOUND CAROTID IMAGE ANALYSIS

Lambrou, A., Papadopoulos, H., Kyriacou, E. C., Pattichis, C. S., Pattichis, M. S., Gammerman, A., & Nicolaides, A. N. (2012) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213012400167 · Cited by 15 · see citing works

System Log Detection Model Based on Conformal Prediction

Ren, Y., Gu, Z., Wang, Z., Tian, Z., Liu, C., Lu, H. D., Du, X., & Guizani, M. (2020) · Electronics · doi:10.3390/electronics9020232 · Cited by 15 · see citing works

Certifiable Object Pose Estimation: Foundations, Learning Models, and Self-Training

Talak, R., Peng, L., & Carlone, L. (2023) · IEEE Transactions on Robotics · doi:10.1109/tro.2023.3271568 · Cited by 15 · see citing works

Uncertainty-aware genomic deep learning with knowledge distillation

Zhou, J., Rizzo, K., Christensen, T. A., Tang, Z., & Koo, P. K. (2026) · npj Artificial Intelligence · doi:10.1038/s44387-025-00053-3 · Cited by 14 · see citing works

The Importance of Being a Band: Finite-Sample Exact Distribution-Free Prediction Sets for Functional Data

Diquigiovanni, J., Fontana, M., & Vantini, S. (2023) · Statistica Sinica · doi:10.5705/ss.202022.0087 · Cited by 14 · see citing works

A reliable breast cancer diagnosis approach using an optimized deep learning and conformal prediction

Almaslukh, B. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106743 · Cited by 14 · see citing works

Calibrated explanations for regression

Löfström, T., Löfström, H., Johansson, U., Sönströd, C., & Matela, R. (2025) · Machine Learning · doi:10.1007/s10994-024-06642-8 · Cited by 14 · see citing works

Signed-Error Conformal Regression

Linusson, H., Johansson, U., & Löfström, T. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-06608-0_19 · Cited by 14 · see citing works

Regression trees for streaming data with local performance guarantees

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Conformal predictions for information fusion

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Reliable Confidence Predictions Using Conformal Prediction

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Reliable Text-to-SQL with Adaptive Abstention

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Conformal load prediction with transductive graph autoencoders

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Reliable pavement backcalculation with confidence estimation

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Qualified Predictions for Large Data Sets

Papadopoulos, H. (2009) · The Knowledge Engineering Review · doi:10.1017/s0269888909990221 · Cited by 2 · see citing works

Ridge Regression Confidence Machine

Nouretdinov, I., Melluish, T., & Vovk, V. (2001) · Cited by 72 · see citing works

Transductive confidence machines

Rogers, J. (2011) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.154 · Cited by 2 · see citing works

On-line confidence machines are well-calibrated

Vovk, V. (2003) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.2002.1181895 · Cited by 49 · see citing works

Transductive Confidence Machine

Nouretdinov, I., & Vovk, V. (2003)