shuangxu96 / IntroVBLinks
An introduction to variational Bayesian
☆24Updated 6 years ago
Alternatives and similar repositories for IntroVB
Users that are interested in IntroVB are comparing it to the libraries listed below
Sorting:
- This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)☆44Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- source code of the paper Graphical Generative Adversarial Networks☆71Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 8 months ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 7 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 6 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆125Updated 6 years ago
- AISTATS 2019: Reference-based Adversarial Sampling & Its applications to Soft Q-learning☆15Updated 6 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- Implementation of the Deep Frank-Wolfe Algorithm -- Pytorch☆62Updated 4 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders☆23Updated 6 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).☆33Updated 5 years ago
- Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"☆121Updated 6 years ago
- code for steinGAN - Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning☆27Updated 6 years ago
- ☆13Updated 7 years ago
- Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.☆28Updated 7 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆44Updated 6 years ago
- Deep Generative Models (Chainer)☆10Updated 7 years ago
- Interpolation between Residual and Non-Residual Networks, ICML 2020. https://arxiv.org/abs/2006.05749☆26Updated 4 years ago
- PyTorch implementation of Neural Processes☆89Updated 6 years ago
- On the decision boundary of deep neural networks☆38Updated 6 years ago
- The code for the ACL 2017 paper "Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling"☆29Updated 8 years ago
- ☆17Updated 7 years ago
- Code release for the ICLR paper☆20Updated 7 years ago
- Wasserstein / earth mover's distance visualizations☆66Updated 8 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago