A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
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Updated
Jun 7, 2024 - Jupyter Notebook
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
A Library for Uncertainty Quantification.
🚩 Conformal Anomaly Detection for PyOD.
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
Code for "Towards Human-AI Complementarity with Predictions Sets", arXiv 2024
Implementation of Conformal Convolution T-learner (CCT) and Conformal Monte Carlo (CMC) learner
Machine Learning with uncertainty quantification and interpretability
Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
Code for "Designing Decision Support Systems Using Counterfactual Prediction Sets". ICML 2024.
Conformal Prediction in Multi-User Settings
Implementation for our paper "Metric-guided Image Reconstruction Bounds via Conformal Prediction".
Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
Code for the paper "Approximating full conformal prediction at scale via influence functions""
All the material needed to use MC-CP and the Adaptive MC Dropout method
Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
In this repo, I implement, compare and reproduce results for different conformal prediction methods for various graph machine learning models.
Code for "Improving Expert Predictions with Prediction Sets" , ICML 2023
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