ENSTA-U2IS-AI / awesome-uncertainty-deeplearning
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
☆670Updated last week
Alternatives and similar repositories for awesome-uncertainty-deeplearning
Users that are interested in awesome-uncertainty-deeplearning are comparing it to the libraries listed below
Sorting:
- Open-source framework for uncertainty and deep learning models in PyTorch☆388Updated this week
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆625Updated 2 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆469Updated last year
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,504Updated 2 weeks ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆587Updated 3 weeks ago
- Learn fast, scalable, and calibrated measures of uncertainty using neural networks!☆472Updated 3 years ago
- Benchmarking Generalized Out-of-Distribution Detection☆956Updated last month
- ☆107Updated 3 years ago
- 👽 Out-of-Distribution Detection with PyTorch☆289Updated last week
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆361Updated 9 months ago
- Laplace approximations for Deep Learning.☆502Updated 3 weeks ago
- Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, boo…☆912Updated last week
- PyTorch implementation of bayesian neural network [torchbnn]☆526Updated 9 months ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆141Updated last year
- ☆237Updated 4 years ago
- A curated list of awesome Active Learning☆764Updated 6 months ago
- Continual Learning papers list, curated by ContinualAI☆630Updated last year
- Bayesian Deep Learning: A Survey☆513Updated 6 months ago
- 2024 up-to-date list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.☆743Updated 4 months ago
- Collection of awesome test-time (domain/batch/instance) adaptation methods☆950Updated last week
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆128Updated 3 years ago
- DomainBed is a suite to test domain generalization algorithms☆1,498Updated 4 months ago
- Lightweight, useful implementation of conformal prediction on real data.☆879Updated last year
- A simple way to calibrate your neural network.☆1,145Updated 3 years ago
- Domain adaptation made easy. Fully featured, modular, and customizable.☆375Updated 2 years ago
- Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning☆178Updated this week
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning☆1,483Updated 2 weeks ago
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆564Updated last year