There are 10 repositories under uncertainty-estimation topic.
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Natural Gradient Boosting for Probabilistic Prediction
Curated list of open source tooling for data-centric AI on unstructured data.
Lightweight, useful implementation of conformal prediction on real data.
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
An extension of XGBoost to probabilistic modelling
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation
An extension of LightGBM to probabilistic modelling
[ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
[CVPR 2022 Oral] Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective than the classifier's own implied confidence (e.g. softmax probability for a neural network).
Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
Quantile Regression Forests compatible with scikit-learn.
An extension of CatBoost to probabilistic modelling
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.
[ICCV'23] Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks
Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, 2022)
(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.
A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
Sandia Uncertainty Quantification Toolkit
Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
Code for paper "Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning"
[ACM MM 2020] Uncertainty-based Traffic Accident Anticipation