A Library for Uncertainty Quantification.

Python package for conformal prediction

A Python toolbox for conformal prediction research on deep learning models, using PyTorch.

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

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.

Public release for "Explore until Confident: Efficient Exploration for Embodied Question Answering"

[ 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"

Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation

A Library for Conformal Hyperparameter Tuning

Unofficial implementation of Conformal Language Modeling by Quach et al

Bayesian optimization with conformal coverage guarantees

[CVPRW 2024] Conformal prediction for uncertainty quantification in image segmentation

Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems

Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.