#Uncertainty
Showing 30 of 30 repositories tagged #uncertainty, ranked by stars
Time series forecasting with PyTorch
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
Lightweight, useful implementation of conformal prediction on real data.
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
A Library for Uncertainty Quantification.
Visualizations of distributions and uncertainty
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
Open-source framework for uncertainty and deep learning models in PyTorch 🌱
A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.
A curated list of trustworthy deep learning papers. Continually updating...
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
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).
[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
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
Density estimation using Gaussian mixtures in the presence of noisy, heterogeneous and incomplete data
Bayesian dessert for Lasagne
(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
(ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models
Some notebooks
Multi Task Learning Implementation with Homoscedastic Uncertainty in Tensorflow
Local explanations with uncertainty 💐!
Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure
Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"
Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration