This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
☆162Jul 23, 2022Updated 4 years ago
Alternatives and similar repositories for Predictive-Uncertainty-Estimation-using-Deep-Ensemble
Users that are interested in Predictive-Uncertainty-Estimation-using-Deep-Ensemble are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆141Jan 15, 2018Updated 8 years ago
- ☆239May 23, 2020Updated 6 years ago
- 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"☆16Mar 5, 2022Updated 4 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆584Feb 26, 2022Updated 4 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- This repository contains an official implementation of LPBNN.☆38Jun 28, 2023Updated 3 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,603Oct 20, 2026Updated 2 weeks ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,979Oct 20, 2023Updated 3 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆641Aug 1, 2022Updated 4 years ago
- Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods☆23Jun 1, 2021Updated 5 years ago
- PyTorch implementation of the original evidental-deep-learning@https://github.com/aamini/evidential-deep-learning/☆13Sep 20, 2021Updated 5 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆521Jan 2, 2024Updated 2 years ago
- Dropout as Regularization and Bayesian Approximation☆57Nov 17, 2018Updated 7 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch 🌱☆531Sep 1, 2026Updated 2 months ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆829Oct 20, 2026Updated 2 weeks ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Feb 16, 2018Updated 8 years ago
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆2,022Mar 5, 2025Updated last year
- Utilities to perform Uncertainty Quantification on Keras Models☆121Feb 24, 2024Updated 2 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆174Apr 12, 2022Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Aug 31, 2020Updated 6 years ago
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆30Nov 28, 2022Updated 3 years ago
- Uncertainty estimation on Mnist dataset☆23Jan 13, 2018Updated 8 years ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆231Jul 25, 2024Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- model uncertainty using mc dropout☆21Mar 1, 2019Updated 7 years ago
- Analysis of evidential models☆15Jun 22, 2023Updated 3 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Nov 19, 2020Updated 5 years ago
- [ICLR 2022] "Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity" by Shiwei Liu,…☆27Jun 15, 2022Updated 4 years ago
- ☆110Jun 29, 2021Updated 5 years ago
- Official code: Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks☆10Jan 23, 2024Updated 2 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆478Jul 6, 2023Updated 3 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆35May 29, 2015Updated 11 years ago
- " Weight Uncertainty in Neural Networks"☆49Jan 31, 2018Updated 8 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆37Nov 29, 2021Updated 4 years ago
- Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. htt…☆13May 25, 2022Updated 4 years ago
- ☆12Mar 19, 2018Updated 8 years ago
- LightProbNets☆26Nov 20, 2019Updated 6 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆362Jun 30, 2017Updated 9 years ago
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆986Sep 25, 2023Updated 3 years ago
- Overview of Bayesian Deep Learning☆11Apr 24, 2019Updated 7 years ago