aangelopoulos / prediction-powered-inferenceLinks
A statistical toolkit for scientific discovery using machine learning
☆80Updated last year
Alternatives and similar repositories for prediction-powered-inference
Users that are interested in prediction-powered-inference are comparing it to the libraries listed below
Sorting:
- A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.☆260Updated last month
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆163Updated last year
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆69Updated 2 years ago
- A package for conformal prediction with conditional guarantees.☆64Updated 7 months ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- Public dataset repository for the Causal Chamber Project☆45Updated 2 months ago
- Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion …☆49Updated 3 weeks ago
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- Active Bayesian Causal Inference (Neurips'22)☆58Updated last year
- Materials of the Nordic Probabilistic AI School 2022.☆179Updated 3 years ago
- Code for multistep feedback covariate shift conformal prediction experiments in "Conformal Validity Guarantees Exist for Any Data Distrib…☆27Updated last year
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆68Updated 7 months ago
- ☆22Updated last year
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆69Updated 10 months ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆85Updated last year
- ☆48Updated 8 months ago
- Extending Conformal Prediction to LLMs☆67Updated last year
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆86Updated last year
- Official Implementation of the paper: "A Rate-Distorion View of Uncertainty Quantification", ICML 2024☆28Updated last year
- Uncertainty quantification with PyTorch☆372Updated last week
- Fast implementation of Venn-ABERS probabilistic predictors☆75Updated last year
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 9 months ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆59Updated last year
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆52Updated last year
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆32Updated 2 years ago