bayesgroup / variational-dropout-sparsifies-dnnLinks
Sparse Variational Dropout, ICML 2017
☆313Updated 5 years ago
Alternatives and similar repositories for variational-dropout-sparsifies-dnn
Users that are interested in variational-dropout-sparsifies-dnn are comparing it to the libraries listed below
Sorting:
- A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).☆206Updated 6 years ago
- ☆133Updated 8 years ago
- A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017☆146Updated 8 years ago
- Decoupled Neural Interfaces using Synthetic Gradients for PyTorch☆238Updated 6 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆208Updated 7 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆48Updated 7 years ago
- Code for "The Reversible Residual Network: Backpropagation Without Storing Activations"☆362Updated 7 years ago
- ☆219Updated 7 years ago
- Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training o…☆149Updated 8 years ago
- Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch☆120Updated 8 years ago
- Implementation of VLAE☆216Updated 7 years ago
- Implements pytorch code for the Accelerated SGD algorithm.☆215Updated 7 years ago
- VQ-VAE implementation / pytorch☆182Updated 7 years ago
- Optimizing control variates for black-box gradient estimation☆163Updated 6 years ago
- Structured Bayesian Pruning, NIPS 2017☆74Updated 5 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆253Updated 6 years ago
- Code to reproduce some of the figures in the paper "On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima"☆145Updated 8 years ago
- ☆252Updated 8 years ago
- Dilated RNNs in pytorch☆212Updated 6 years ago
- Generative moment matching networks☆151Updated 9 years ago
- an implementation of L0 regularization with PyTorch☆57Updated 7 years ago
- categorical variational autoencoder using the Gumbel-Softmax estimator☆432Updated 8 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆103Updated 9 years ago
- Learning kernels to maximize the power of MMD tests☆210Updated 7 years ago
- TensorNet (TensorFlow implementation)☆213Updated 8 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- Implementation of "Learning with Random Learning Rates" in PyTorch.☆102Updated 5 years ago
- Fast Scattering Transform with CuPy/PyTorch☆294Updated 5 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- auto-tuning momentum SGD optimizer☆288Updated 6 years ago