TENGBINN / Bayes-by-Backprop
TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
☆51Updated 6 years ago
Alternatives and similar repositories for Bayes-by-Backprop:
Users that are interested in Bayes-by-Backprop are comparing it to the libraries listed below
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 6 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- Denoising Adversairal Autoencoders☆40Updated 7 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- Professor Forcing, NIPS'16☆45Updated 8 years ago
- ☆16Updated 8 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Updated 10 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- ☆62Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- Deep variational inference in tensorflow☆56Updated 6 years ago
- The code for the ACL 2017 paper "Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling"☆29Updated 7 years ago
- ZForcing Repo☆40Updated 7 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago
- Implementation of the Incremental Sequence Learning algorithms described in the Incremental Sequence Learning article☆40Updated 7 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago