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Conformal prediction is a statistical framework that generates prediction sets containing ground-truth labels with a desired coverage guarantee.
Inductive confidence machines for regression
Papadopoulos, H., Proedrou, K., Vovk, V., and Gammerman, A · 2002
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On-line confidence machines are well-calibrated
Vovk, V · 2002
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Algorithmic learning in a random world , volume 29
Vovk, V., Gammerman, A., and Shafer, G · 2005
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A tutorial on conformal prediction
Shafer, G. and Vovk, V · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
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Learning multiple layers of features from tiny images
Krizhevsky, A., Hinton, G., et al · 2009
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Conditional validity of inductive conformal predictors
Vovk, V · 2012
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Applications of class-conditional conformal predictor in multi-class classification
Shi, F., Ong, C. S., and Leckie, C · 2013
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Uncertainty quantification: theory, implementation, and applications , volume 12
Smith, R. C · 2013
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Conformal prediction for reliable machine learning: theory, adaptations and applications
Balasubramanian, V., Ho, S.-S., and Vovk, V · 2014
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Distribution-free prediction bands for non-parametric regression
Lei, J. and Wasserman, L · 2014
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A cross-conformal predictor for multi-label classification
Papadopoulos, H · 2014
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Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission
Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., and Elhadad, N · 2015
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A conformal prediction approach to explore functional data
Lei, J., Rinaldo, A., and Wasserman, L · 2015
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Bias reduction through conditional conformal prediction
Löfström, T., Boström, H., Linusson, H., and Johansson, U · 2015
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Cross-conformal predictors
Vovk, V · 2015
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End to end learning for self-driving cars
Bojarski, M., Del Testa, D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L. D., Monfort, M., Muller, U., Zhang, J., et al · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Gal, Y. and Ghahramani, Z · 2016
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Hendrycks, D. and Gimpel, K · 2016
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On calibration of modern neural networks
Guo, C., Pleiss, G., Sun, Y., and Weinberger, K. Q · 2017
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Do imagenet classifiers generalize to imagenet?
Recht, B., Roelofs, R., Schmidt, L., and Shankar, V · 2019
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Conformalized quantile regression
Romano, Y., Patterson, E., and Candes, E · 2019
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Least ambiguous set-valued classifiers with bounded error levels
Sadinle, M., Lei, J., and Wasserman, L · 2019
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Conformal prediction under covariate shift
Tibshirani, R. J., Foygel Barber, R., Candes, E., and Ramdas, A · 2019
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Training conformal predictors
Colombo, N. and Vovk, V · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al · 2020
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Classification with valid and adaptive coverage
Romano, Y., Sesia, M., and Candes, E · 2020
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Node classification with bounded error rates
Wijegunawardana, P., Gera, R., and Soundarajan, S · 2020
Cited alongside, same era.
A gentle introduction to conformal prediction and distribution-free uncertainty quantification
Angelopoulos, A. N. and Bates, S · 2021
Cited alongside, same era.
Uncertainty sets for image classifiers using conformal prediction
Angelopoulos, A. N., Bates, S., Jordan, M. I., and Malik, J · 2021
Cited alongside, same era.
Predictive inference with the jackknife+
Barber, R. F., Candès, E. J., Ramdas, A., and Tibshirani, R. J · 2021
Cited alongside, same era.
Distribution-free, risk-controlling prediction sets
Bates, S., Angelopoulos, A., Lei, L., Malik, J., and Jordan, M · 2021
Cited alongside, same era.
Optimized conformal classification using gradient descent approximation
Class-conditional conformal prediction with many classes
Ding, T., Angelopoulos, A. N., Bates, S., Jordan, M. I., and Tibshirani, R. J · 2023
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Conformal prediction is robust to dispersive label noise
Feldman, S., Einbinder, B.-S., Bates, S., Angelopoulos, A. N., Gendler, A., and Romano, Y · 2023
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Improving uncertainty quantification of deep classifiers via neighborhood conformal prediction: Novel algorithm and theoretical analysis
Ghosh, S., Belkhouja, T., Yan, Y., and Doppa, J. R · 2023
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Conformal prediction with conditional guarantees
Gibbs, I., Cherian, J. J., and Candès, E. J · 2023
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Conformal prediction with large language models for multi-choice question answering
Kumar, B., Lu, C., Gupta, G., Palepu, A., Bellamy, D., Raskar, R., and Beam, A · 2023
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Bellotti, A · 2021
Cited alongside, same era.
Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction
Cauchois, M., Gupta, S., and Duchi, J. C · 2021
Cited alongside, same era.
Learning prediction intervals for regression: Generalization and calibration
Chen, H., Huang, Z., Lam, H., Qian, H., and Zhang, H · 2021
Cited alongside, same era.
Few-shot conformal prediction with auxiliary tasks
Fisch, A., Schuster, T., Jaakkola, T., and Barzilay, R · 2021
Cited alongside, same era.
The limits of distribution-free conditional predictive inference
Foygel Barber, R., Candes, E. J., Ramdas, A., and Tibshirani, R. J · 2021
Cited alongside, same era.
Adversarially robust conformal prediction
Gendler, A., Weng, T.-W., Daniel, L., and Romano, Y · 2021
Cited alongside, same era.
Distribution-free uncertainty quantification for classification under label shift
Podkopaev, A. and Ramdas, A · 2021
Cited alongside, same era.
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Conformal inference is (almost) free for neural networks trained with early stopping
Liang, Z., Zhou, Y., and Sesia, M · 2023
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Federated conformal predictors for distributed uncertainty quantification
Lu, C., Yu, Y., Karimireddy, S. P., Jordan, M., and Raskar, R · 2023
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Group-conditional conformal prediction via quantile regression calibration for crop and weed classification
Melki, P., Bombrun, L., Diallo, B., Dias, J., and Da Costa, J.-P · 2023
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Conformal prediction for federated uncertainty quantification under label shift
Plassier, V., Makni, M., Rubashevskii, A., Moulines, E., and Panov, M · 2023
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Quach, V., Fisch, A., Schuster, T., Yala, A., Sohn, J. H., Jaakkola, T. S., and Barzilay, R · 2023
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Robots that ask for help: Uncertainty alignment for large language model planners
Ren, A. Z., Dixit, A., Bodrova, A., Singh, S., Tu, S., Brown, N., Xu, P., Takayama, L., Xia, F., Varley, J., et al · 2023
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Adaptive conformal classification with noisy labels
Sesia, M., Wang, Y. R., and Tong, X · 2023
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Improving expert predictions with conformal prediction
Straitouri, E., Wang, L., Okati, N., and Rodriguez, M. G · 2023
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How to trust your diffusion model: A convex optimization approach to conformal risk control
Teneggi, J., Tivnan, M., Stayman, W., and Sulam, J · 2023
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Predictive inference with feature conformal prediction
Teng, J., Wen, C., Zhang, D., Bengio, Y., Gao, Y., and Yuan, Y · 2023
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Wang, J., Tong, J., Tan, K., Vorobeychik, Y., and Kantaros, Y · 2023
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Safe merging in mixed traffic with confidence
Bang, H., Dave, A., and Malikopoulos, A. A · 2024
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Conformal prediction sets improve human decision making
Cresswell, J. C., Sui, Y., Kumar, B., and Vouitsis, N · 2024
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Colep: Certifiably robust learning-reasoning conformal prediction via probabilistic circuits
Kang, M., Gürel, N. M., Li, L., and Li, B · 2024
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Moya, C., Mollaali, A., Zhang, Z., Lu, L., and Lin, G · 2024
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Out-of-distribution detection should use conformal prediction (and vice-versa?)
Novello, P., Dalmau, J., and Andeol, L · 2024
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Conformalized physics-informed neural networks
Podina, L., Rad, M. T., and Kohandel, M · 2024
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Training-conditional coverage bounds under covariate shift, 2024
Pournaderi, M. and Xiang, Y · 2024
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Similarity-navigated conformal prediction for graph neural networks
Song, J., Huang, J., Jiang, W., Zhang, B., Li, S., and Wang, C · 2024
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Api is enough: Conformal prediction for large language models without logit-access
Su, J., Luo, J., Wang, H., and Cheng, L · 2024
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Does confidence calibration help conformal prediction?
Xi, H., Huang, J., Feng, L., and Wei, H · 2024
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Robust conformal prediction under distribution shift via physics-informed structural causal model
Xu, R., Sun, Y., Chen, C., Venkitasubramaniam, P., and Xie, S · 2024
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