paraschopra / bayesian-neural-network-mnistLinks
Bayesian neural network using Pyro and PyTorch on MNIST dataset
☆315Updated 7 years ago
Alternatives and similar repositories for bayesian-neural-network-mnist
Users that are interested in bayesian-neural-network-mnist are comparing it to the libraries listed below
Sorting:
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 6 years ago
- Building a Bayesian deep learning classifier☆493Updated 8 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- Bayesian Deep Learning Benchmarks☆671Updated 2 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆577Updated 3 years ago
- Papers for Bayesian-NN☆326Updated 6 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆246Updated 6 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆360Updated 6 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆476Updated 2 years ago
- MLSS2019 Tutorial on Bayesian Deep Learning☆93Updated 6 years ago
- a repo sharing Bayesian Neural Network recent papers☆216Updated 6 years ago
- Bayesian Neural Network in PyTorch☆93Updated last year
- ☆239Updated 5 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Updated 7 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- Learning error bars for neural network predictions☆72Updated 5 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆253Updated 7 years ago
- ☆251Updated 3 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆206Updated 3 years ago
- Bayesian neural network package☆154Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆102Updated 7 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆635Updated 3 years ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆122Updated 6 years ago
- This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural P…☆1,010Updated 4 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated last week
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- ☆275Updated 5 years ago