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65 search results found

Awesome Conformal Prediction ⭐ 3,097

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

Ngboost ⭐ 1,543

Natural Gradient Boosting for Probabilistic Prediction

Uncertainty Toolbox ⭐ 1,421

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

Fortuna ⭐ 824

A Library for Uncertainty Quantification.

Xgboostlss ⭐ 453

An extension of XGBoost to probabilistic modelling

Bayesian Torch ⭐ 396

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

Mono Uncertainty ⭐ 201

CVPR 2020 - On the uncertainty of self-supervised monocular depth estimation

👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.

Lightgbmlss ⭐ 179

An extension of LightGBM to probabilistic modelling

GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation

Conformal Predictions From Scratch ⭐ 118

Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.

Udr S2former_deraining ⭐ 102

[ICCV'23] Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks

Masksembles ⭐ 90

Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR2021).

Evaluating_bdl ⭐ 70

Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.

Quantile Forest ⭐ 70

Quantile Regression Forests compatible with scikit-learn.

Sandia Uncertainty Quantification Toolkit

Natural Posterior Network ⭐ 59

Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, 2022)

Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors

Code for paper "Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning"

Surface_normal_uncertainty ⭐ 54

(ICCV 2021 - oral) Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

[ACM MM 2020] Uncertainty-based Traffic Accident Anticipation

Spatial Smoothing ⭐ 51

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

(CVPR 2022 - oral) Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry

Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

Monodepth Uncertainty ⭐ 39

Inferring distributions over depth from a single image, IROS 2019

Conffusion ⭐ 37

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

Code for "Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors." (ICLR 2021)

This repository contains an official implementation of LPBNN.

Distinction Maximization Loss ⭐ 34

Improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.

Conformal Risk ⭐ 33

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

Nlp Uncertainty Zoo ⭐ 32

Model zoo for different kinds of uncertainty quantification methods used in Natural Language Processing, implemented in PyTorch.

Relative Uncertainty Learning ⭐ 31

Relative Uncertainty Learning

Grumodepth ⭐ 30

Gradient-based Uncertainty for Monocular Depth Estimation (ECCV 2022)

Im2im Uq ⭐ 29

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.

Graph Posterior Network ⭐ 27

Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)

Zero Shot Counting ⭐ 26

CVPR2023 Zero-shot Counting

Conformal Metalearners ⭐ 26

[ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"

Muad Dataset ⭐ 23

MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks [BMVC 2022]

Uncrtaints ⭐ 23

Slex Net ⭐ 22

[IEEE-JBHI'2022] Hematoma Expansion Context Guided Intracranial Hemorrhage Segmentation and Uncertainty Estimation(Pytorch)

Noisy K Fac ⭐ 20

Natural Gradient, Variational Inference

pyPCGA: fast and scalable inverse modeling approach

ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models

Densereconstruction Pytorch ⭐ 15

Official Repo for the paper "Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment" (MICCAI 2020)

Pycaplunar ⭐ 13

pyCAPLunar is a python package to determine the moment tensor of earthquake sources and their uncertainty by using the 3D receiver-side SGT database.

Mose Auseg ⭐ 13

The official code repo for the paper "Mixture of Stochastic Experts for Modeling Aleatoric Uncertainty in Segmentation". (ICLR 2023)

Py Boostlss ⭐ 13

An extension of Py-Boost to probabilistic modelling

Transmission Bvm ⭐ 12

Dataset and code of our AAAI2022 paper "Transmission-Guided Bayesian Generative Model for Smoke Segmentation"

Data-driven risk-conscious thermoelectric materials discovery

Mimo Unet ⭐ 10

PyTorch implementation of Probabilistic MIMO U-Net

Uncertainty Estimation Diabeticretinopathy ⭐ 10

Estimating uncertainty of neural networks for automated screening of Diabetic Retinopathy using the PyTorch framework. Generated visual explanation of the deep learning system to convey the pixels in the image that influences its decision Integrated Gradient method.

Robust Deep Learning ⭐ 9

Train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.

Official implementation of SEDNet (CVPR 2023)

Deeplabv3plus Muad Pytorch ⭐ 8

Deeplab V3+ on the MUAD dataset

Structural Graph Shifts ⭐ 8

Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts (NeurIPS 2023)

Deep Split Ensembles ⭐ 8

Why have a Unified Uncertainty? Disentangling it using Deep Split Ensembles

Regression_uncertainty ⭐ 8

Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", 2023.

Dum Components ⭐ 6

Training, Architecture, and Prior for Deterministic Uncertainty Methods (ICLR 2023 Workshop on Trustworthy ML)

NOMU: Neural Optimization-based Model Uncertainty

Slurp_uncertainty_estimate ⭐ 6

The implementations for SLURP: Side Learning Uncertainty for Regression Problems (BMVC 2021)

Plotting Uncertainty Ellipses ⭐ 5

This Jupyter notebook demonstrates how to properly plot uncertainty (confidence) ellipses for 2D normally distributed data.

Layerensembles ⭐ 5

The source code for the Layer Ensembles paper published in MICCAI 2022 (Singapore).

Calibrated Bert Fine Tuning ⭐ 5

Code for Paper: Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data

MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction

Plausible Uncertainties ⭐ 5

Methods used in the paper "Plausible Uncertainties for Human Pose Regression".

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