Anastasios Angelopoulos

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).

aangelopoulos

Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"

aangelopoulos

Lightweight, useful implementation of conformal prediction on real data.

aangelopoulos

Implementation of https://arxiv.org/abs/2003.08592

aangelopoulos

Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vision and natural language processing.

aangelopoulos

Dataset release for Event-Based, Near-Eye Gaze Tracking Beyond 10,000 Hz

aangelopoulos

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

aangelopoulos

Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

aangelopoulos

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

aangelopoulos

A statistical toolkit for scientific discovery using machine learning

aangelopoulos