There are 9 repositories under conformal-prediction topic.
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
Lightweight, useful implementation of conformal prediction on real data.
Python package for conformal prediction
Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
Conformal prediction for time-series applications.
Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction for time-series (journal, IEEE TPAMI)
đź‘– Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
Valid and adaptive prediction intervals for probabilistic time series forecasting
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vision and natural language processing.
[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"
Conditional calibration of conformal p-values for outlier detection.
Code for paper "Copula-based conformal prediction for Multi-Target Regression"
Unofficial implementation of Conformal Language Modeling by Quach et al
Bayesian optimization with conformal coverage guarantees
Public release for "Explore until Confident: Efficient Exploration for Embodied Question Answering"
Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms
Adaptive Conformal Prediction Intervals (ACPI) is a Python package that enhances the Predictive Intervals provided by the split conformal approach by employing a weighting strategy.
All the material needed to use MC-CP and the Adaptive MC Dropout method
Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
PAC-Bayes generalization certificates for ICP
An introduction to conformal prediction
SSCP: Improving Adaptive Conformal Prediction Using Self-supervised Learning (AISTATS 2023)