aangelopoulos / conformal-riskLinks
Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vision and natural language processing.
☆71Updated 2 years ago
Alternatives and similar repositories for conformal-risk
Users that are interested in conformal-risk are comparing it to the libraries listed below
Sorting:
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆70Updated 11 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 3 years ago
- A package for conformal prediction with conditional guarantees.☆66Updated 3 weeks ago
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated last year
- Extending Conformal Prediction to LLMs☆68Updated last year
- Unofficial implementation of Conformal Language Modeling by Quach et al☆29Updated 2 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆33Updated 2 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆250Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Large-scale uncertainty benchmark in deep learning.☆63Updated 5 months ago
- relplot: Utilities for measuring calibration and plotting reliability diagrams☆170Updated 3 months ago
- Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"☆13Updated last year
- A statistical toolkit for scientific discovery using machine learning☆80Updated last year
- Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems☆22Updated 3 years ago
- ☆17Updated 2 months ago
- Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"☆59Updated last week
- Influence Estimation for Gradient-Boosted Decision Trees☆30Updated last year
- Neural Additive Models (Google Research)☆73Updated 4 years ago
- Code for multistep feedback covariate shift conformal prediction experiments in "Conformal Validity Guarantees Exist for Any Data Distrib…☆27Updated last year
- For calculating Shapley values via linear regression.☆71Updated 4 years ago
- ☆109Updated 3 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆86Updated last year
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- ModelDiff: A Framework for Comparing Learning Algorithms☆59Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- ☆11Updated last month