google-deepmind / conformal_training
This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classifiers".
☆120Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for conformal_training
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆59Updated last year
- A library for uncertainty quantification based on PyTorch☆119Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆86Updated last year
- Bayesianize: A Bayesian neural network wrapper in pytorch☆86Updated 5 months ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆86Updated 9 months ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆76Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆63Updated 5 months ago
- relplot: Utilities for measuring calibration and plotting reliability diagrams☆133Updated 4 months ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆37Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆52Updated last month
- A statistical toolkit for scientific discovery using machine learning☆70Updated 4 months ago
- A package for conformal prediction with conditional guarantees.☆47Updated 3 months ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆159Updated 5 months ago
- Euclidean Wasserstein-2 optimal transportation☆43Updated last year
- ☆141Updated last year
- Our maintained PFN repository. Come here to train SOTA PFNs.☆46Updated this week
- Extending Conformal Prediction to LLMs☆57Updated 4 months ago
- Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…☆146Updated last year
- Parameter-Free Optimizers for Pytorch☆108Updated 6 months ago
- A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.☆205Updated this week
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆140Updated 3 months ago
- Transformers with doubly stochastic attention☆40Updated 2 years ago
- ☆18Updated last year
- ☆97Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2022.☆171Updated 2 years ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆49Updated last year
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆227Updated last year
- ☆109Updated 2 years ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆115Updated 3 years ago