AlaaLab / deep-learning-uncertainty
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
☆616Updated 2 years ago
Alternatives and similar repositories for deep-learning-uncertainty:
Users that are interested in deep-learning-uncertainty are comparing it to the libraries listed below
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆456Updated last year
- ☆228Updated 4 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆271Updated 2 years ago
- Papers for Bayesian-NN☆318Updated 5 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,476Updated this week
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆564Updated 2 years ago
- Bayesian Deep Learning: A Survey☆508Updated 2 months ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆449Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆152Updated 2 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆505Updated 5 months ago
- Building a Bayesian deep learning classifier☆487Updated 7 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆561Updated last week
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆352Updated 5 months ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆606Updated last month
- ☆235Updated 2 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆173Updated 2 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆338Updated this week
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Bayesian Deep Learning Benchmarks☆666Updated last year
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆210Updated 5 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,871Updated last year
- Learn fast, scalable, and calibrated measures of uncertainty using neural networks!☆450Updated 3 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,471Updated 8 months ago
- ☆99Updated 3 years ago
- PyTorch code to run synthetic experiments.☆415Updated 3 years ago
- A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.☆793Updated 3 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆143Updated 2 years ago
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆941Updated last year
- A simple way to calibrate your neural network.☆1,124Updated 3 years ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆227Updated 5 months ago