My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
☆141Jan 15, 2018Updated 8 years ago
Alternatives and similar repositories for deep-ensembles-uncertainty
Users that are interested in deep-ensembles-uncertainty are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Dec 18, 2016Updated 9 years ago
- This repo contains a PyTorch implementation of the paper: "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles"☆17Mar 5, 2022Updated 4 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Feb 16, 2018Updated 8 years ago
- Reproduction of the paper: Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles☆27Dec 4, 2019Updated 6 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆582Feb 26, 2022Updated 4 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- ☆15Mar 24, 2016Updated 10 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,591Updated this week
- ☆41May 14, 2019Updated 7 years ago
- Uncertainty interpretations of the neural network☆32May 3, 2018Updated 8 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Apr 8, 2020Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Aug 31, 2020Updated 6 years ago
- This is official code for "Combating Label Distribution Shift for Active Domain Adaptation" accepted in ECCV2022☆15Oct 25, 2022Updated 3 years ago
- Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.☆134Jul 4, 2020Updated 6 years ago
- model uncertainty using mc dropout☆21Mar 1, 2019Updated 7 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Jul 17, 2020Updated 6 years ago
- ☆239May 23, 2020Updated 6 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆479Jul 6, 2023Updated 3 years ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆230Jul 25, 2024Updated 2 years ago
- A Pytorch implementation of Diffusion-Based Probabilistic Uncertainty Estimation for Active Domain Adaptation☆16Nov 28, 2023Updated 2 years ago
- A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.☆66Jun 26, 2020Updated 6 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆39Dec 15, 2017Updated 8 years ago
- ☆11Sep 16, 2023Updated 2 years ago
- [Under Progress] Code & Data for the AAAI 2020 Paper "Likelihood Ratios and Generative Classifiers For Unsupervised OOD Detection In Task…☆10Jul 25, 2024Updated 2 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆362Jun 30, 2017Updated 9 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,969Oct 20, 2023Updated 2 years ago
- A curated list of resources dedicated to bayesian deep learning☆416May 10, 2017Updated 9 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆273May 5, 2018Updated 8 years ago
- Modeling uncertainty information in deep learning☆22Jan 11, 2018Updated 8 years ago
- Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"☆25May 1, 2019Updated 7 years ago
- pytorch implementation for paper, towards realistic predictors☆17Sep 26, 2018Updated 7 years ago
- Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf☆30Jan 15, 2020Updated 6 years ago
- Papers for Bayesian-NN☆327Jun 25, 2019Updated 7 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆23Jan 27, 2022Updated 4 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,570Apr 19, 2024Updated 2 years ago
- rich posterior approximations and anomaly detection☆20Mar 15, 2019Updated 7 years ago
- Blog for the Open Institute for Advanced Study☆10Oct 30, 2020Updated 5 years ago
- [ICML 2024] Official code for Uncertainty Estimation by Density Aware Evidential Deep Learning☆17Mar 20, 2026Updated 5 months ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Feb 24, 2016Updated 10 years ago
- Lecture notes on Bayesian deep learning☆487Feb 11, 2018Updated 8 years ago