mirceamironenco / BayesianRecurrentNNLinks
Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al
☆218Updated 6 years ago
Alternatives and similar repositories for BayesianRecurrentNN
Users that are interested in BayesianRecurrentNN are comparing it to the libraries listed below
Sorting:
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 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
- Tools for loading standard data sets in machine learning☆204Updated 2 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- Deep generative models for semi-supervised learning.☆108Updated 8 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 11 months ago
- A variational recurrent neural network implementation in tensorflow☆104Updated 7 years ago
- ☆62Updated 8 years ago
- Tensorflow implementation for DilatedRNN☆350Updated 7 years ago
- Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0☆128Updated 6 years ago
- Keras implementation of Phased LSTM [https://arxiv.org/abs/1610.09513]☆144Updated 5 years ago
- ☆291Updated 7 years ago
- Bayesian Weight Uncertainty Dense Layer for Keras☆48Updated 8 years ago
- Tensorflow implementation of a Hierarchical and Multiscale RNN, described in https://arxiv.org/abs/1609.01704☆135Updated 7 years ago
- Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution☆51Updated 7 years ago
- Gumbel-Softmax Variational Autoencoder with Keras☆132Updated 7 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- supercell☆192Updated 7 years ago
- Structured Inference Networks for Nonlinear State Space Models☆272Updated 7 years ago
- Code for paper "L4: Practical loss-based stepsize adaptation for deep learning"☆124Updated 6 years ago
- Implementation of Sequential Variational Autoencoder☆88Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Benchmark and build RL architectures that can do multitask and transfer learning.☆143Updated 2 years ago
- Dropout As A Bayesian Approximation: Code☆202Updated 10 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 3 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Classification uncertainty using Bayesian neural networks☆33Updated 9 years ago
- Forward Thinking NIPS 2017☆106Updated 7 years ago