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.
☆611Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for deep-learning-uncertainty
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆454Updated last year
- ☆226Updated 4 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆268Updated 2 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,452Updated last month
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆555Updated 2 years ago
- Papers for Bayesian-NN☆314Updated 5 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆150Updated 2 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆438Updated 10 months ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆576Updated last month
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆540Updated 9 months ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆305Updated this week
- ☆235Updated last year
- Bayesian Deep Learning: A Survey☆505Updated last week
- PyTorch implementation of bayesian neural network [torchbnn]☆496Updated 3 months ago
- Building a Bayesian deep learning classifier☆486Updated 7 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
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆170Updated 2 years ago
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆207Updated 4 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆347Updated 3 months ago
- Bayesian Deep Learning Benchmarks☆663Updated last year
- ☆97Updated 3 years ago
- Learn fast, scalable, and calibrated measures of uncertainty using neural networks!☆439Updated 3 years ago
- Laplace approximations for Deep Learning.☆471Updated this week
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,844Updated last year
- A simple way to calibrate your neural network.☆1,104Updated 3 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,437Updated 7 months ago
- Bayesian neural network using Pyro and PyTorch on MNIST dataset☆308Updated 5 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 6 years ago
- PyTorch code to run synthetic experiments.☆413Updated 3 years ago