uncertainty-neural-networks

Here are 30 public repositories matching this topic...

IntelLabs / bayesian-torch

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

deep-neural-networks deep-learning pytorch uncertainty-neural-networks bayesian-inference uncertainty-quantification uncertainty-estimation bayesian-neural-networks bayesian-deep-learning stochastic-variational-inference bayesian-layers

Updated Feb 10, 2024
Python

dougbrion / pytorch-classification-uncertainty

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This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

paper pytorch uncertainty mnist classification mnist-classification uncertainty-neural-networks torchvision evidential-deep-learning dirichlet-distributions

Updated Jan 2, 2024
Python

mattiasegu / uncertainty_estimation_deep_learning

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This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, Segù, Scaramuzza. RA-L 2020).

deep-learning uncertainty-neural-networks

Updated Jul 25, 2024
Python

vvanirudh / deep-ensembles-uncertainty

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My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"

deep-learning tensorflow uncertainty uncertainty-neural-networks

Updated Jan 15, 2018
Python

nikitadurasov / masksembles

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Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).

computer-vision deep-learning tensorflow paper torch uncertainty-neural-networks uncertainty-quantification uncertainty-estimation out-of-distribution-detection

Updated Feb 8, 2024
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IntelLabs / AVUC

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

deep-learning uncertainty-neural-networks model-calibration uncertainty-quantification uncertainty-estimation variational-inference bayesian-deep-learning probabilistic-neural-network probabilistic-deep-learning uncertainty-calibration

Updated Dec 16, 2022
Python

Kaleidophon / nlp-uncertainty-zoo

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

python nlp package deep-learning transformers pytorch lstm rnn uncertainty-neural-networks uncertainty-quantification uncertainty-estimation nlp-machine-learning

Updated May 5, 2023
Python

testingautomated-usi / uncertainty-wizard

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Uncertainty-Wizard is a plugin on top of tensorflow.keras, allowing to easily and efficiently create uncertainty-aware deep neural networks. Also useful if you want to train multiple small models in parallel.

testing keras uncertainty uncertainty-neural-networks uncertainty-quantification keras-tensorflow

Updated May 24, 2023
Python

gengshan-y / monodepth-uncertainty

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Inferring distributions over depth from a single image, IROS 2019

deep-learning tensorflow uncertainty-neural-networks uncertainty-estimation monocular-depth

Updated Jul 21, 2023
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alexrakowski / mc-dropout-mnist

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Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf

deep-learning keras mnist uncertainty-neural-networks mc-dropout bayesian-convnets

Updated Jan 15, 2020
Python

cantarinigiorgio / HHP-Net

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[WACV'22] Official implementation of "HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty"

deep-learning neural-network uncertainty-neural-networks head pose-estimation

Updated Mar 9, 2022
Python

ptrckhmmr / DEAL

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Code for "Deal: Deep Evidential Active Learning for Image Classification" (ICMLA 2020)

cnn image-classification uncertainty-neural-networks active-learning

Updated Apr 27, 2021
Python

antonbaumann / MIMO-Unet

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PyTorch implementation of Probabilistic MIMO U-Net

uncertainty-neural-networks uncertainty-quantification uncertainty-estimation uncertainty-analysis u-net deep-ensemble

Updated Aug 15, 2024
Python

dlmacedo / robust-deep-learning

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A project to 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.