kyle-dorman / bayesian-neural-network-blogpostLinks
Building a Bayesian deep learning classifier
☆486Updated 7 years ago
Alternatives and similar repositories for bayesian-neural-network-blogpost
Users that are interested in bayesian-neural-network-blogpost are comparing it to the libraries listed below
Sorting:
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆573Updated 3 years ago
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 5 years ago
- Bayesian Deep Learning Benchmarks☆671Updated 2 years ago
- Bayesian neural network using Pyro and PyTorch on MNIST dataset☆313Updated 6 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆628Updated 2 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- Papers for Bayesian-NN☆323Updated 5 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,500Updated last year
- ☆238Updated 5 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆465Updated last year
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆210Updated 5 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- a repo sharing Bayesian Neural Network recent papers☆216Updated 5 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,894Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆154Updated 2 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆251Updated 6 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆138Updated 7 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆348Updated 7 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆533Updated 10 months ago
- A curated list of resources dedicated to bayesian deep learning☆415Updated 8 years ago
- Lecture notes on Bayesian deep learning☆484Updated 7 years ago
- Active Learning on Image Data using Bayesian ConvNets☆138Updated 8 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆150Updated 2 years ago