google / uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
☆1,448Updated 3 weeks ago
Related projects ⓘ
Alternatives and complementary repositories for uncertainty-baselines
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆609Updated 2 years ago
- ☆466Updated 3 months ago
- A simple way to calibrate your neural network.☆1,097Updated 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 …☆345Updated 3 months ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆436Updated 10 months ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆565Updated last month
- Bayesian Deep Learning Benchmarks☆662Updated last year
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,589Updated 2 years ago
- Laplace approximations for Deep Learning.☆468Updated last month
- A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.☆550Updated 9 months ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆302Updated last week
- Learn fast, scalable, and calibrated measures of uncertainty using neural networks!☆436Updated 3 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆451Updated last year
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆531Updated 8 months ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆268Updated 2 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,833Updated last year
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆1,823Updated 4 months ago
- Toolbox of models, callbacks, and datasets for AI/ML researchers.☆1,691Updated this week
- A simple probabilistic programming language.☆679Updated 2 weeks ago
- DomainBed is a suite to test domain generalization algorithms☆1,404Updated 3 months ago
- Pytorch Lightning code guideline for conferences☆1,239Updated last year
- PyTorch implementation of bayesian neural network [torchbnn]☆489Updated 3 months ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,431Updated 6 months ago
- Cockpit: A Practical Debugging Tool for Training Deep Neural Networks☆474Updated 2 years ago
- Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)☆1,814Updated 3 months ago
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆561Updated 6 months ago
- Bayesian active learning library for research and industrial usecases.☆865Updated 4 months ago
- A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch☆1,982Updated last year
- disentanglement_lib is an open-source library for research on learning disentangled representations.☆1,384Updated 3 years ago
- PyTorch code to run synthetic experiments.☆413Updated 3 years ago