The most comprehensive professionally curated list of Awesome Conformal Prediction tutorials, videos, books, papers and open-source libraries in Python and R.
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Why Conformal Prediction?
One of the most influential and celebrated machine learning researchers - Professor Michael I. Jordan:
'𝗖𝗼𝗻𝗳𝗼𝗿𝗺𝗮𝗹 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗶𝗱𝗲𝗮𝘀 𝗮𝗿𝗲 𝗧𝗛𝗘 𝗮𝗻𝘀𝘄𝗲𝗿 𝘁𝗼 𝗨𝗤 (𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻), 𝗜 𝘁𝗵𝗶𝗻𝗸 𝗶𝘁'𝘀 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗜 𝗵𝗮𝘃𝗲 𝘀𝗲𝗲𝗻 - 𝗶𝘁𝘀 𝘀𝗶𝗺𝗽𝗹𝗲, 𝗴𝗲𝗻𝗲𝗿𝗮𝗹𝗶𝘀𝗮𝗯𝗹𝗲 𝗲𝘁𝗰.' (ICML 2021 UQ workshop). 🔥🔥🔥🔥🔥
One the most influential statistics Professors - Larry Wasserman (Carnegie Mellon):
'𝗦𝗼 𝘁𝗵𝗲 𝗯𝗲𝗮𝘂𝘁𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗰𝗼𝗻𝗳𝗼𝗿𝗺𝗮𝗹 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗵𝗼𝘄 𝘀𝗶𝗺𝗽𝗹𝗲 𝗶𝘁 𝗶𝘀 𝘁𝗼 𝗱𝗼 𝗶𝘁 𝗮𝗻𝗱 𝗵𝗼𝘄 𝗴𝗲𝗻𝗲𝗿𝗮𝗹 𝗶𝘁 𝗶𝘀. 𝗦𝗼 𝗜 𝘁𝗵𝗶𝗻𝗸 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗶𝗱𝗲𝗮𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝘁𝗰𝗵 𝗼𝗻, 𝗴𝗲𝗻𝗲𝗿𝗮𝗹 𝗶𝗱𝗲𝗮𝘀 𝘁𝗵𝗮𝘁 𝗮𝗿𝗲 𝗽𝗿𝗲𝘁𝘁𝘆 𝗴𝗲𝗻𝗲𝗿𝗮𝗹 𝗮𝗻𝗱 𝐞𝐚𝐬𝐲 𝐭𝐨 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐭𝐡𝐚𝐭 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐩𝐢𝐜𝐭𝐮𝐫𝐞 𝐲𝐨𝐮𝐫𝐬𝐞𝐥𝐟 𝐮𝐬𝐢𝐧𝐠 𝐢𝐧 𝐫𝐞𝐚𝐥 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐫𝐞𝐚𝐬𝐨𝐧 𝐭𝐡𝐚𝐭 𝐩𝐞𝐨𝐩𝐥𝐞 𝐮𝐬𝐢𝐧𝐠 𝐜𝐨𝐧𝐟𝐨𝐫𝐦𝐚𝐥 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧.' 🚀🚀🚀🚀🚀
https://slideslive.com/icml-2021/workshop-on-distributionfree-uncertainty-quantification
When both the top machine learning and the top statistic professors from the best research labs in the world say this about conformal prediction it is quite an endorsement.
In 2022 conformal prediction research experienced exponential growth in academia and with the availability of open-source libraries the industry is positioned to replicate this growth in the industry.
📢📢Industry take notice. The revolution in Uncertainty Quantification / Probabilistic Prediction / Forecasting is already here 📢📢 A big one 🔥🔥🔥🔥🔥
🌟 🌟 🌟 🌟 🌟
Featured resources:
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
This is the newest version of the super-popular tutorial on Conformal Prediction (over 3,500 stars on YouTube) now significantly expanded (2x), including advanced techniques such as covariate shift conformal, as well as a super fun history and literature review in Section 7.
A Tutorial on Conformal Prediction by Anastasios Angelopoulos and Stephen Bates (2021) 🔥🔥🔥🔥🔥
A Tutorial on Conformal Prediction Part 2: Conditional Coverage and Diagnostics by Anastasios Angelopoulos and Stephen Bates (2022)
⭐⭐️⭐️⭐️⭐️
- Algorithmic Learning in a Random World by Vladimir Vovk and Alex Gammerman, also Glenn Shafer (2005). Second edition in progress. 🔥🔥🔥🔥🔥
- Conformal Prediciton for Reliable Machine Learning by Vineeth Balasubramanian, Shen-Shyang Ho, Vladimir Vovk (2014) 🔥🔥🔥🔥🔥
- Conformal predictive distributions with kernels by Vladimir Vovk, Ilia Nouretdinov, Valery Manokhin, Alex Gammerman (Chapter in 'Braverman Readings in Machine Learning. Key Ideas from Inception to Current State', Springer, 2018). 🔥🔥🔥🔥🔥
- Confidence, Likelihood, Probability by Tore Schweder and Nils Lid Hjort (University of Oslo, 2016). Not directly about Conformal Prediction but a great book about modern frequentist methods. 🔥🔥🔥🔥🔥
- Conformal and Venn Predictors for large, imbalanced and sparse chemoinformatics data by Paolo Toccaceli (Royal Holloway, UK, 2021)
- Competitive online algorithms for probabilistic prediction by Raisa Dzhamtyrova (Royal Holloway, UK, 2020)
- Conformal Prediction and Testing under On-line Compression Models by Valentina Fedorova (Royal Holloway, UK, 2014)
- Adaptive Online Learning by Dmitry Adamskiy (Royal Holloway, UK, 2013)
- On discovery and exploitation of temporal structure in data sets by Scarfe, Tim (Royal Holloway, UK, 2015)
- Black-box Security Measuring Black-box Information Leakage via Machine Learning by Giovanni Cherubin (Royal Holloway, UK, 2019)
- Small and Large Scale Probabilistic Classifiers with Guarantees of Validity by Ivan Petej (Royal Holloway, UK, 2019)
- Towards a Question Answering View of Natural Language Processing by Zukov Gregoric, Andrej (Royal Holloway, UK, 2019)
- Confidence and Venn Machines and Their Applications to Proteomics by Devetyarov, Dmitry (Royal Holloway, UK, 2019)
- Conformal Anomaly Detection - detecting abnormanl trajectories in surveillance applications by Rikard Laxhammar (University of Skoeve, Sweden, 2014)
- Inductive Confidence Machine for Pattern Recognition - is it the next step towards AI by David Surkov (Royal Holloway, UK, 2004)
- Distribution Free Prediction Intervals for Multiple Functional Regression by Ryan Kelly (University of Pittsburgh, 2020).
- Probabilistic Load Forecasting with Deep Conformalized Quantile Regression by Vilde Jensen (Artcic University of Norway, 2021)
- A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification by Anastasios N. Angelopoulos and Stephen Bates (2021) 🔥🔥🔥🔥🔥
- A Tutorial on Conformal Prediction by Anastasios Angelopoulos and Stephen Bates (2021) 🔥🔥🔥🔥🔥
- A Tutorial on Conformal Predictive Distributions by Paolo Toccaceli (2020) 🔥🔥🔥🔥🔥
- Conformal Prediciton Tutorial by Henrik Linusson (2021) 🔥🔥🔥🔥🔥
- Henrik Linusson: Conformal Prediction by Henrik Linusson (2020)
- Predicting with Confidence - Henrik Boström by Henrik Boström (2016)
- Venn Predictors Tutorial by Ulf Johansson, Cecilia Sönströd, Tuve Löfström, and Henrik Boström (2021)
- Ulf Johansson: Venn Predictors by Ulf Johansson (2020)
- A Tutorial on Conformal Prediction by Glenn Shafer and Vladimir Vovk (2008) 🔥🔥🔥🔥🔥
- Conformal Prediction: a Unified Review of Theory and New Challenges by Gianluca Zeni, Matteo Fontana1 and Simone Vantini (Politecnico di Milano, Italy, 2021)
- Conformal Prediction in Spark by Marco Capuccini (Uppsala University, 2017)
- Tutorial on Venn-ABERS prediction by Paolo Toccaceli (Royal Holloway, UK, 2017) 🔥🔥🔥🔥🔥
- An Introduction to Conformal Prediction by Henrik Linusson (2017) 🔥🔥🔥🔥🔥
- Introduction to Conformal Prediction by Vineeth N Balasubramanian (Indian Ins)tute of Technology, Hyderabad, 2015)
- Conformal prediction A Tiny Tutorial on Predicting with Confidence by Henrik Linusson and Ulf Johansson (2014)
- Treatment of Uncertainty in the Foundations of Probability by Vladimir Vovk (Royal Holloway, UK, 2017)
- Large-Scale Probabilistic Prediction With and Without Validity Guarantees by Vladimir Vovk (Royal Holloway, UK, NeurIPS 2015) 🔥🔥🔥🔥🔥
- Conformal testing in a binary model situation by Vladimir Vovk (Royal Holloway, UK, 2021)
- Protected probabilistic classification by Vladimir Vovk (Royal Holloway, UK, 2021)
- Retrain or not retrain: conformal test martingales for change-point detection by Vladimir Vovk (Royal Holloway, UK, 2021) 🔥🔥🔥🔥🔥
- A Tutorial on Conformal Prediction by Anastasios Angelopoulos and Stephen Bates (Berkeley, ICML 2021) 🔥🔥🔥🔥🔥
- Steps Toward Trustworthy Machine Learning by Tom Dietterich (2021)
- A Tutorial on Conformal Predictive Distributions by Paolo Toccaceli (Royal Holloway, UK, 2020) 🔥🔥🔥🔥🔥
- Conformal Prediciton Tutorial by Henrik Linusson (2021) 🔥🔥🔥🔥🔥
- Henrik Linusson: Conformal Prediction by Henrik Linusson (2020)
- Predicting with Confidence - Henrik Boström by Henrik Boström (2016)
- How to increase certainty in predictive modeling by Emmanuel Candes (Stanford, 2021) 🔥🔥🔥🔥🔥
- Recent Progress in Predictive Inference by Emmanuel Candes (Stanford, 2020) 🔥🔥🔥🔥🔥
- Some recent progress in predictive inference" (Stanford) @ MAD+ by Emmanuel Candes (Stanford, 2020)
- Conformal Prediciton in 2020 by Emmanuel Candes (Stanford, 2020) 🔥🔥🔥🔥🔥
- Assumption-free prediction intervals for black-box regression algorithms by Aaditya Ramdas (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
- Maria Navarro: Quantifying uncertainty in Machine Learning predictions | PyData London 2019 by Maria Navarro (2019)
- Conformal Prediction: Enhanced Method for Understanding the Prediction Quality by Artem Ryasik and Greg Landrum
- Venn Predictors Tutorial by Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, and Henrik Boström (2021)
- Mondrian conformal predictive distributions by Henrik Boström, Ulf Johansson, and Tuwe Löfström (2021) 🔥🔥🔥🔥🔥
- Calibrating Multi-Class Models by Ulf Johansson, Tuwe Löfström, and Henrik Boström (2021)
- Conformal testing in a binary model situation by Vladimir Vovk (Royal Holloway, UK, 2021)
- Conformal prediction in Orange by Tomaž Hočevar and Blaž Zupan (2021)
- Distribution-Free, Risk-Controlling Prediction Sets by Anastasios Angelopoulos (Stanford, 2021) 🔥🔥🔥🔥🔥
- Conformal Prediction and Distribution-Free Calibration by Aaditya Ramdas (Carnegie Mellon, 2021) 🔥🔥🔥🔥🔥
- Reliable Diagnostics by Conformal Predictors by Alexander Gammerman (Royal Holloway, UK, 2015)
- Distribution-Free, Risk-Controlling Prediction Sets by Anastasios Angelopoulos (Stanford, 2021) 🔥🔥🔥🔥🔥
- Conformal Inference of Counterfactuals and Time-to-event Outcomes by Lihua Lei (Stanford, 2021)
- Algo Hour – Conformal Inference of Counterfactuals and Individual Treatment Effect by Lihua Lei (Stanford, 2021)
- Conformal Inference of Counterfactuals and Individual Treatment effects(Stanford) by Lihua Lei (Stanford, 2021)
- Approximation to object conditional validity with inductive conformal predictors by Anthony Bellotti (University of Nottingham Ningbo, China, 2021)
- Ulf Johansson: Venn Predictors by Ulf Johansson (Jönköping University, Sweden, 2021) 🔥🔥🔥🔥🔥
- Transformer-based conformal predictors for paraphrase detection by Patrizio Giavannotti and Prof. Alexander Gammerman (Royal Holloway, UK, 2021)
- Conformal Inference of Counterfactuals and Individual Treatment Effects by Lihua Lei (Stanford, 2020)
- Model-Free Predictive Inference by Larry Wasserman (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
- Shapley-value based inductive conformal prediction by William Lopez Jaramillo (2021)
- Conformal Training: Learning Optimal Conformal Classifiers | DeepMind by David Stutz (2021) 🔥🔥🔥🔥🔥
- Distribution-Free, Risk-Controlling Prediction Sets by Anastasios Angelopoulos (2021) 🔥🔥🔥🔥🔥
- Assumption-Free, High-Dimensional Inference by Larry Wasserman (2016)
- Neural Predictive Monitoring under Partial Observability by Francesca Cairolli (2021)
- Conformalized Kernel Ridge Regression and Its Efficiency by Evgeny Burnaev (Skolkovo, Russia, 2015)
- Fast conformal classification using influence functions by Giovanni Cherubin (Alan Turing Institute, UK, 2021)
- Valid inferential models and conformal prediction by Ryan Martin (North Carolina State University, USA, 2021)
- Mondrian conformal predictive distributions by Henrik Boström, Ulf Johansson and Tuwe Löfström (KTH Royal Institute of Technology, Sweden, 2021) 🔥🔥🔥🔥🔥
- Evaluation of updating strategies for conformal predictive systems in the presence of extreme events by Hugo Werner, Lars Carlsson, Ernst Ahlberg and and Henrik Boström (KTH Royal Institute of Technology, Sweden, 2021)
- Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data by Victor Chernozhukov (MIT, USA, 2019) 🔥🔥🔥🔥🔥
- Ulf Johansson: Venn Predictors by Ulf Johansson (Jönköping University, Sweden, 2020) 🔥🔥🔥🔥🔥
- Class-wise confidence for debt prediction in real estate management by Soundouss Messoudi (2021)
- How Nonconformity Functions and Difficulty of Datasets Impact the Efficiency of Conformal Classifiers by Marharyta Aleksandrova (2021)
- Nested conformal prediction and quantile out-of-bag ensemble methods by Chirag Gupta (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
- Panel with Michael I. Jordan, Vladimir Vovk, and Larry Wasserman, moderated by Aaditya Ramdas by Vladimir Vovk, Larry Wasserman, Michael I. Jordan, Aaditya Ramdas, ICML 2021 🔥🔥🔥🔥🔥 🔥🔥🔥🔥🔥
- Black-box uncertainty - Anastasios Angelopoulos by Anastasios Angelopoulos (Berkeley, USA, 2021) 🔥🔥🔥🔥🔥
- P.C. Mahalanobis Memorial Lectures 2020-21 by Vladimir Vovk (Royal Holloway, UK, 2021)
- Rahul Vishwakarma: New Perspective on Machine Learning Predictions Under Uncertainty | SNIA Storage Developer Conference, Santa Clara 2019 by Rahul Vishwakarma (2019)
- Fast conformal classification using influence functions by Umang Bhatt, Adrian Weller and Giovanni Cherubin (Cambridge / Alan Turinig Institute, 2021).
- Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination by Ulf Norinder, Lars Carlsson, Scott Boyer, and Martin Eklund (2014)
- Uncertainty Sets for Image Classifiers using Conformal Prediction by Anastasios N. Angelopoulos, Stephen Bates, Jitendra Malik, & Michael I. Jordan (Berkeley, 2021) 🔥🔥🔥🔥🔥
- Conformal Prediction Under Covariate Shift by Ryan Tibshirani, Rina Foygel Barber, Emmanuel Candes, Aaditya Ramdas (Carnegie Mellon, Stanford, Chicago, 2019) 🔥🔥🔥🔥🔥
- Regression Conformal Prediction with Nearest Neighbours by Harris Papadopoulos, Vladimir Vovk and Alex Gammerman (Royal Holloway, UK, 2014)
- Nested conformal prediction and quantile out-of-bag ensemble methods by Chirag Gupta, Arun Kuchibhotla and Aaditya Ramdas (Carnegie Mellon, 2021) 🔥🔥🔥🔥🔥
- Cross-conformal predictive distributions by Vladimir Vovk, Ilia Nouretdinov, Valery Manokhin and Alexander Gammerman (Royal Holloway, UK, 2018) 🔥🔥🔥🔥🔥 🔥🔥🔥🔥🔥
- Criteria of Efficiency for Conformal Prediction by Vladimir Vovk, Ilia Nouretdinov, Valentina Fedorova, Ivan Petej, and Alex Gammerman ((Royal Holloway, UK, 2016)
- Conformal Prediction for Simulation Models by Benjamin LeRoy and Chad Schafer (Carnegie Mellon, 2021)
- Distribution-free, risk-controlling prediction sets Stephen Bates, Anastasios Angelopoulos, Lihua Lei, Jitendra Malik and Michael I Jordan (Berkeley, 2021) 🔥🔥🔥🔥🔥
- Conditional calibration for false discovery rate control under dependence by William Fithian and Lihua Lei (Stanford, 2021)
- Conformal Prediction: a Unified Review of Theory and New Challenges by Gianluca Zeni, Matteo Fontana and S. Vantini (2021) 🔥🔥🔥🔥🔥
- Regression conformal prediction with random forests by Ulf Johansson, Henrik Boström, Tuve Löfström and Henrik Linusson (2014)
- A conformal prediction approach to explore functional data by Jing Lei, Alessandro Rinaldo, Larry Wasserman (Carnegie Mellon, 2013)
- An electronic nose-based assistive diagnostic prototype for lung cancer detection with conformal prediction by Xianghao Zhana,c, Zhan Wanga, Meng Yangb, Zhiyuan Luod, You Wanga, Guang Li (2020)
- Predicting the Rate of Skin Penetration Using an Aggregated Conformal Prediction Framework by Martin Lindh, A. Karlén, Ulf Norinder (2017)
- The application of conformal prediction to the drug discovery process by Martin Eklund, Ulf Norinder, Scott Boyer & Lars Carlsson (2014) 🔥🔥🔥🔥🔥
- Distributional conformal prediction by Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu (2021) 🔥🔥🔥🔥🔥
- Anomaly Detection of Trajectories with Kernel Density Estimation by Conformal Prediction by James Smith, Ilia Nouretdinov, Rachel Craddock, Charles Offer, and Alexander Gammerman (2009)
- Conformal prediction interval estimation and applications to day-ahead and intraday power markets by Christopher Kath, Florian Ziel (2019) 🔥🔥🔥🔥🔥
- The application of conformal prediction to the drug discovery process by Martin Eklund, Ulf Norinder, Scott Boyer & Lars Carlsson (2013)
- Anomaly Detection of Trajectories with Kernel Density Estimation by Conformal Prediction by James Smith, Ilia Nouretdinov, Rachel Craddock, Charles Offer, Alexander Gammerman (Royal Holloway, UK, 2014)
- Conformal Prediction: a Unified Review of Theory and New Challenges by Gianluca Zeni, Matteo Fontana1 and Simone Vantini (Politecnico di Milano, Italy, 2021)
- Exchangeability, Conformal Prediction, and Rank Tests by Arun Kuchibhotla (Carnegie Mellon, 2021)
- Conformal prediction with localization by Leying Guan (Yale, 2020)
- Predicting skin sensitizers with confidence - Using conformal prediction to determine applicability domain of GARD by Andy Forreryd, Ulf Norinder, Tim Lindberg, Malin Lindstedt (2018)
- Binary classification of imbalanced datasets using conformal prediction by Ulf Norinder, Scott Boyer (2017)
- Discretized conformal prediction for efficient distribution-free inference by Wenyu Chen, Kelli-Jean Chun, and Rina Foygel Barber (2017)
- Validity, consonant plausibility measures, and conformal prediction by Leonardo Cella. and Ryan Martin (2021)
- Conformal Prediction Classification of a Large Data Set of Environmental Chemicals from ToxCast and Tox21 Estrogen Receptor Assays by Ulf Norinder, Scott Boyer (2016)
- Conformal prediction to define applicability domain – A case study on predicting ER and AR binding by U. Norinder, A. Rybacka, P.Andersson (2016)
- Conformal prediction of biological activity of chemical compounds by Paolo Toccaceli, Ilia Nouretdinov, Alex Gammerman (Royal Holloway, UK, 2017) 🔥🔥🔥🔥🔥
- Introducing conformal prediction in predictive modeling for regulatory purposes. A transparent and flexible alternative to applicability domain determination by Ulf Norinder, Lars Carlsson, Scott Boyer, Martin Eklund (2015)
- Aggregated Conformal Prediction by Lars CarlssonMartin EklundUlf Norinder (2014)
- Interpretation of Conformal Prediction Classification Models by Ernst Ahlberg, Ola Spjuth, Catrin Hasselgren, Lars Carlsson (2015)
- Cross-Conformal Prediction with Ridge Regression by Harris Papadopoulos (2015)
- Sparse conformal prediction for dissimilarity data by Frank-Michael Schleif, Xibin Zhu and Barbara Hammer (2015)
- Effective utilization of data in inductive conformal prediction using ensembles of neural networks by Tuve Löfström, Ulf Johansson and Henrik Boström (2013)
- Beyond the Basic Conformal Prediction Framework by Vladimir Vovk (2014)
- An electronic nose-based assistive diagnostic prototype for lung cancer detection with conformal prediction by Xianghao Zhan, Zhan Wang, Meng Yang, Zhiyuan Luo, You Wang, Guang Li (Stanford, Royal Holloway, China University of Mining and Technology, 2020)
- Predicting with confidence: Using conformal prediction in drug discovery by Jonathan Alvarsson, Staffan Arvidsson McShane, Ulf Norinder, Ola Spjuth (2021)
- Inductive conformal prediction for silent speech recognition by Ming Zhang, You Wang, Zhang Wei, Meng Yang, Zhiyuan Luo, Guang Li (2020)
- Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery by Nicolas Bosc, Francis Atkinson, Eloy Felix, Anna Gaulton, Anne Hersey and Andrew R. Leach (2019)
- Deep Conformal Prediction for Robust Models by Soundouss Messoudi, Sylvain Rousseau and Sébastien Destercke (2020)
- Strong validity, consonance, and conformal prediction by Leonardo Cella and Ryan Martin (2020)
- Skin Doctor CP: Conformal Prediction of the Skin Sensitization Potential of Small Organic Molecules by Anke Wilm, U. Norinder, M. Agea, Christina de Bruyn Kops, Conrad Stork, J. Kühnl, J. Kirchmair (2020)
- Conformal prediction based active learning by linear regression optimization by Sergio Matiz, Kenneth E.Barner (2020)
- Conformal prediction intervals for the individual treatment effect by Danijel Kivaranovic, Robin Ristl, Martin Poschb, Hannes Leeb (2020)
- Nearest neighbor based conformal prediction by László Györfi and Harro Walk (2020)
- Concepts and Applications of Conformal Prediction in Computational Drug Discovery by Isidro Cortés-Ciriano and Andreas Bender (2019) 🔥🔥🔥🔥🔥
- Predicting Ames Mutagenicity Using Conformal Prediction in the Ames/QSAR International Challenge Project by Ulf Norinder, Ernst Ahlberg, Lars Carlsson (2018)
- Nested Conformal Prediction and the Generalized Jackknife by Arun Kuchibhotla and Aaditya Ramdas (Carnegie Mellon, 2019)
- Predictive inference with the jackknife+ by Rina Foygel Barber, Emmanuel Candès, Aaditya Ramdas, and Ryan Tibshirani (2020) 🔥🔥🔥🔥🔥
- Nonparametric predictive distributions based on conformal prediction by Vladimir Vovk, Jieli Shen, Valery Manokhin and Min-ge Xie (Royal Holloway, UK, Rutgers, USA, 2018) 🔥🔥🔥🔥🔥
- A Distribution-Free Test of Covariate Shift Using Conformal Prediction by Xiaoyu Hu and Jing Lei (Peking Univerity, China and Carnegie Mellon, USA, 2020) 🔥🔥🔥🔥🔥
- Exchangeability, Conformal Prediction, and Rank Tests by Arun Kuchibhotla (Carnegie Mellon, 2021)
- Conformal prediction with localization by Leying Guan (2020)
- Multitask Modeling with Confidence Using Matrix Factorization and Conformal Prediction by Ulf Norinder, Fredrik Svensson
- Conformal prediction of HDAC inhibitors by U. Norinder, J.J.Navaka, E. Lopez-Lopez, D. Mucs & J.L. Medina-Franco (2019)
- Computing Full Conformal Prediction Set with Approximate Homotopy by Eugene Ndiaye, Ichiro Takeuchi (2019)
- Conformal Prediction Based on Raman Spectra for the Classification of Chinese Liquors by Jiao Gu, Huaibo Liu, Chaoqun Ma, Lei Li, Chun Zhu, Christ Glorieux, Guoqing Chen (2019)
- Efficient and minimal length parametric conformal prediction regions by Daniel Eck and Forrest Crawford (2019)
- Conformal Prediction for Students' Grades in a Course Recommender System by Raphael Morsomme and Evgueni Smirnov (2019)
- Efficient iterative virtual screening with Apache Spark and conformal prediction by Laeeq Ahmed, Valentin Georgiev, Marco Capuccini, Salman Toor, Wesley Schaal, Erwin Laure and Ola Spjuth (2018)
- Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction by Samuel Lampa, Jonathan Alvarsson, Staffan Arvidsson Mc Shane, Arvid Berg, Ernst Ahlberg, Ola Spjuth (2018)
- Maximizing gain in high-throughput screening using conformal prediction by Fredrik Svensson, Avid M. Afzal1, Ulf Norinder and Andreas Bender (2018)
- Conformalized Survival Analysis by Emmanuel Candès, Lihua Lei and Zhimei Ren (2021) 🔥🔥🔥🔥🔥
- Random Forest Prediction Intervals by Haozhe Zhang†, Joshua Zimmerman†, Dan Nettleton† and Daniel J. Nordman† (Iowa State University, USA, 2019)
- Conformal Training: Learning Optimal Conformal Classifiers | DeepMind by David Stutz (DeepMind), Krishnamurthy Dvijotham, Ali Taylan Cemgil and Arnaud Doucet (2021)
- Comparing the Bayes and typicalness frameworks by Thomas Melluish, Craig Saunders, Ilia Nouretdinov, and Volodya Vovk (Royal Holloway, UK, 2001). 🔥🔥🔥🔥🔥
- Large-scale probabilistic predictors with and without guarantees of validity by Vladimir Vovk, Ivan Petej, and Valentina Fedorova (Royal Holloway, Yandex, NeurIPS) 🔥🔥🔥🔥🔥
- Inductive conformal prediction for silent speech recognition by Ming Zhang, You Wang, Wei Zhang, Meng Yang, Zhiyuan Luo and Guang Li (2020)
- Conformal Prediction using Conditional Histograms by Matteo Sesia and Yaniv Romano (NeurIPS 2021 paper). 🔥🔥🔥🔥🔥
- Valid prediction intervals for regression problems by Nicolas Dewolf, Bernard De Baets, Willem Waegeman (2021) 🔥🔥🔥🔥🔥
- Application of conformal prediction interval estimations to market makers’ net positions by Wojciech Wisniewski, David Lindsay, Sian Lindsay (Royal Holloway, UK, 2020)
- Locally Valid and Discriminative Prediction Intervals for Deep Learning Models by Zhen Lin, Shubhendu Trivedi, Jimeng Sun (NeurIPS, 2021) 🔥🔥🔥🔥🔥
- Distribution-Free Federated Learning with Conformal Predictions by Charles Lu and Jayashree Kalpathy-Cramer (2022)
- Coreset-based Conformal Prediction for Large-scale Learning by Nery Riquelme-Granada, Khuong Nguyen, Zhiyuan Luo (Royal Holloway, UK, 2019)
- Fast probabilistic prediction for kernel SVM via enclosing balls by Nery Riquelme-Granada, Khuong Nguyen, Zhiyuan Luo (Royal Holloway, UK, 2020)
- Conformalized density- and distance-based anomaly detection in time-series data by Evgeny Burnaev, Vladislav Ishimtsev (2016)
- Predictive Inference with Weak Supervision by Maxime Cauchois, Suyash Gupta, Alnur Ali and John Duchi (Stanford, 2022)
- Conformal Prediction in Clinical Medical Sciences by Janette Vazquez and Julio C. Facelli University of Utah, 2022)
- Provably Improving Expert Predictions with Conformal Prediction by Eleni Straitouri, Lequng Wang, Nastaran Okati and Manuel Gomez Rodriguez (Max Planck Institute for Software Systems / Cornell University, 2021).
- Conformal predictive distributions with kernels by Vladimir Vovk, Ilia Nouretdinov, Valery Manokhin, Alex Gammerman (Royal Holloway, UK, 2017)
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors by Valery Manokhin (Royal Holloway, UK, 2017).
- Computationally efficient versions of conformal predictive distributions by Vladimir Vovk, Ivan Petej, Ilia Nouretdinov, Valery Manokhin, Alex Gammerman (Royal Holloway, UK, 2019).
- Cover your cough: detection of respiratory events with confidence using a smartwatch by Khuong An Nguyen, Zhiyuan Luo (Royal Holloway, 2019).
- Predicting Amazon customer reviews with deep confidence using deep learning and conformal prediction by Ulf Norinder and Petra Norinder (2022)
- Conformal Prediction for the Design Problem by Clara Fannjianga, Stephen Batesa, Anastasios Angelopoulosa, Jennifer Listgartena and Michael I. Jordan (Berkeley, 2022) 🔥🔥🔥🔥🔥
- Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging by Anastasios N. Angelopoulos, Amit Kohli, Stephen Bates, Michael I. Jordan, Jitendra Malik, Thayer Alshaabi, Srigokul Upadhyayula, Yaniv Romano (Berkeley and Technion, 2022) 🔥🔥🔥🔥🔥
- Conformal predictive decision making by Vladimir Vovk and Claus Bendtsen (2018).
- The Lifecycle of a Statistical Model: Model Failure Detection, Identification, and Refitting by Alnur Ali1, Maxime Cauchois and John C. Duchi (Stanford, 2022)
- E-values: Calibration, combination, and applications by Vladimir Vovk (Royal Holloway) and Ruodu Wang (University of Waterloo) (2019)
- Conformal Prediction Sets with Limited False Positives by Adam Fisch, Tal Schuster, Tommi Jaakkola and Regina Barzilay (MIT / Google Research, 2022)
- Adaptive Conformal Predictions for Time Series by Margaux Zaffran, Aymeric Dieuleveut, Olivier Fe ́ron, Yannig Goude, and Julie Josse (EDF / INRIA / CMAP, France, 2022) 🔥🔥🔥🔥🔥
- Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting by Vilde Jensen, Filippo Maria Bianchi∗, Stian Norman Anfinsen (Arctic University of Norway, 2022)
- Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors by Staffan Arvidsson, Ola Spjuth, Lars Carlsson and Paolo Toccaceli (University of Uppsala, Astra Zeneca, Royal Holloway, 2017)
- Probabilistic Prediction in scikit-learn by Sweidan, Dirar and Ulf Johansson.
- Adaptive Conformal Anomaly Detection for Time-series by Evgeny Burnaev, Alexander Bernstein, Vlad Ishimtsev and Ivan Nazarov (Skoltech, Moscow, Russia, 2017)
- Nonparametric predictive distributions based on conformal prediction by Vladimir Vovk, Jieli Shen, Valery Manokhin, Min-ge Xie, Ilia Nouretdinov and Alex Gammerman (Royal Holloway, University of London Rutgers University, 2017)
- What Can Conformal Inference Offer to Statistics? by Lihua Lei, Stanford University
- Vladimir Vovk, Royal Holloway, United Kingdom
- Alexander Gammerman, Royal Holloway, United Kingdom
- Glenn Shafer, Rutgers University, USA
- Emmanuel Candès, Stanford, USA
- Ryan Tibshiriani, Carnegie Mellon, USA
- Yaniv Romano, Technion—Israel Institute of Technology
- Michael I. Jordan, Berkeley, USA
- Jitendra Malik, Berkeley, USA
- Anastasios Angelopoulos, Berkeley, USA
- Lihua Lei, Stanford, USA
- Henrik Boström, KTH, Sweden
- Ulf Johansson, Jönköping University, Sweden
- Henrik Linusson, University of Borås, Sweden
- Harris Papadopoulos, Frederick University, Cyprus
- Vladimir V'yugin, Institute for Information Transmission Problems (IITP), Russia
- Evgeny Burnaev, Skoltech, Russia
- Aaditya Ramdas, Carnegie Mellon, USA
- Benjamin LeRoy, Carnegie Mellon, USA
- Victor Chernozhukov, MIT, USA
- Ulf Norinder, Stockholm University, Sweden
- Ola Spjuth, Uppsala University, Sweden
- Ilia Nouretdinov, Royal Holloway, United Kingdom
- Measuring Models' Uncertainty: Conformal Prediction by Leo Dreyfus-Schmidt (Dataiku, 2020). 🔥🔥🔥🔥🔥
- Conformal Prediction for Neural Regression Model by Pranab Ghosh (2021). 🔥🔥🔥🔥🔥
- How to Handle Uncertainty in Forecasts by Michael Berk (2021)
- How to Add Uncertainty Estimation to your Models with Conformal Prediction by Zachary Warnes (2021)
- nonconformist: An easy way to estimate prediction intervals by Maria Jesus Ugarte (2021).
- Detecting Weird Data: Conformal Anomaly Detection by Matthew Burruss (2020).
- “MAPIE” Explained Exactly How You Wished Someone Explained to You by Samuele Mazzanti (2022). 🔥🔥🔥🔥🔥
- With MAPIE, uncertainties are back in machine learning by Vianney Taquet (2021) 🔥🔥🔥🔥🔥
- How to Predict Risk-Proportional Intervals with Conformal Quantile Regression by by Samuele Mazzanti (2022). 🔥🔥🔥🔥🔥
- Main website with research from Prof. Vladimir (Volodya) Vovk 🔥🔥🔥🔥🔥
- Conformal Prediction - Prediction with guaranteed performance Royal Holloway, United Kingdom
- A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification by Anastasios N. Angelopoulos 🔥🔥🔥🔥🔥
- Reliable Predictive Inference by Yaniv Romano 🔥🔥🔥🔥🔥
- Title: What Can Conformal Inference Offer to Statistics? by Lihua Lei, Stanford, 2022
- [Conformalized survival analysis](https://twitter.com/lihua_lei_stat/status/1381418936739098630?s=20&t=PnfV8wnLV2bThXcKdFFbRg
- https://icml.cc/Conferences/2021/ScheduleMultitrack?event=8373 🔥🔥🔥🔥🔥
- https://cml.rhul.ac.uk/copa2021/ 🔥🔥🔥🔥🔥
- https://cml.rhul.ac.uk/copa2020/ 🔥🔥🔥🔥🔥
- https://cml.rhul.ac.uk/copa2019/ 🔥🔥🔥🔥🔥
- https://cml.rhul.ac.uk/copa2018/ 🔥🔥🔥🔥🔥
- https://cml.rhul.ac.uk/copa2017/ 🔥🔥🔥🔥🔥
- Nonconformist by Henrik Linusson (2015) 🔥🔥🔥🔥🔥
- Venn-ABERS Predictor by Paolo Toccaceli (2019), based on NeurIPS 2015 paper 'Large-scale probabilistic predictors with and without guarantees of validity' (#69 on papers list) 🔥🔥🔥🔥🔥
- MAPIE - Model Agnostic Prediction Interval Estimator (2021) 🔥🔥🔥🔥🔥
- 'Crêpes' - Conformal regressors and predictive systems by Henrik Boström (2021)
- Conformalized Quantile Regression by Yaniv Romano (2019) 🔥🔥🔥🔥🔥
- Conformal Classification by Anastasios N. Angelopoulos (2021)
- Orange3 Conformal Prediction
- EnbPI by Chen Xu (2021) TIME SERIES 🚀🚀🚀🚀🚀 🔥🔥🔥🔥🔥
- Conformal: an R package to calculate prediction errors in the conformal prediction framework by Isidro Cortes, 2019
- Copula Conformal Multi Target Regression by Soundouss Messoudi (2021)
- Uncertainty Toolbox by Youngseog Chung, Willie Neiswanger, Ian Char and Han Guo (2021)
- Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems by Mateo Sesia and Yaniv Romano (NeurIPS 2021). 🔥🔥🔥🔥🔥
- Conformalized density- and distance-based anomaly detection in time-series data (KNN-CAD) by Evgeny Burnaev, Vladislav Ishimtsev (2016). Top #3 winning solution in Numenta competition 🔥🔥🔥🔥🔥
- TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch (2022)
- Conformal time-series forecasting" by Kamile ̇ Stankeviciute (Cambridge, NeurIPS 2021) TIME SERIES 🚀🚀🚀🚀🚀 🔥🔥🔥🔥🔥
- Conformal Inference R Project maintained by Ryan Tibshirani (2016) 🔥🔥🔥🔥🔥
- Prediction Bands by Rafael Izbicki and Benjamin LeRoy (2019)
- Conformal: an R package to calculate prediction errors in the conformal prediction framework by Isidro Cortes, 2019
- Online Time Series Anomaly Detectors by Alaine Iturria, 2021 🔥🔥🔥🔥🔥
- piRF - Prediction Intervals for Random Forests by Chancellor Johnstone and Haozhe Zhang (2019)
- conformalClassification: Transductive and Inductive Conformal Predictions for Classification Problems by Niharika Gauraha and Ola Spjuth (2019)
- RandomForest by Henrik Boström (2017) 🔥🔥🔥🔥🔥
- LibCP -- A Library for Conformal Prediction 🔥🔥🔥🔥🔥
- An Implementation of Venn-ABERS predictor 🔥🔥🔥🔥🔥
- LibVM -- A Library for Venn Machine
- Scala-CP by Marco Capuccini (2017)' 🔥🔥🔥🔥🔥 (see tutorial section 'Conformal Prediction in Spark')