JACKHAHA363 / BBBRNNLinks
Bayesian Backprop RNN implementation pytorch https://arxiv.org/abs/1704.02798
☆25Updated 7 years ago
Alternatives and similar repositories for BBBRNN
Users that are interested in BBBRNN are comparing it to the libraries listed below
Sorting:
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 9 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Experiments for the Neural Autoregressive Flows paper☆124Updated 4 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 7 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Lagrangian VAE☆28Updated 6 years ago
- ZForcing Repo☆40Updated 7 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- Deep Generative Models with Stick-Breaking Priors☆95Updated 9 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Hypergradient descent☆149Updated last year