yaringal / ConcreteDropout
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
☆251Updated 6 years ago
Alternatives and similar repositories for ConcreteDropout
Users that are interested in ConcreteDropout are comparing it to the libraries listed below
Sorting:
- Dropout As A Bayesian Approximation: Code☆201Updated 9 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 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
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 9 months ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆137Updated 7 years ago
- Deep neural network kernel for Gaussian process☆203Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Tensorflow implementation of Hyperspherical Variational Auto-Encoders☆230Updated 6 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 7 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆572Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al☆218Updated 6 years ago
- A PyTorch library for two-sample tests☆239Updated last year
- Papers for Bayesian-NN☆322Updated 5 years ago
- Sparse Variational Dropout, ICML 2017☆313Updated 4 years ago
- Hypergradient descent☆146Updated 11 months ago
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- Implementation of Sequential Variational Autoencoder☆88Updated 7 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆125Updated 6 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆461Updated last year