kefirski / variational_dropout
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
☆49Updated 7 years ago
Alternatives and similar repositories for variational_dropout:
Users that are interested in variational_dropout are comparing it to the libraries listed below
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- The Deep Weight Prior, ICLR 2019☆44Updated 3 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 3 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…☆72Updated 7 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling☆91Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"☆121Updated 6 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- This repository is no longer maintained. Check☆81Updated 4 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 7 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction…☆62Updated 8 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Experiments for the Neural Autoregressive Flows paper☆123Updated 3 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago
- Autoregressive Energy Machines☆77Updated 2 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago