wittawatj / interpretable-test
NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
☆63Updated 6 years ago
Alternatives and similar repositories for interpretable-test:
Users that are interested in interpretable-test are comparing it to the libraries listed below
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 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
- ☆40Updated 5 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 6 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆100Updated 9 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 4 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- Deep Generative Models with Stick-Breaking Priors☆95Updated 8 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Implementation of "Variational Inference for Monte Carlo Objectives"☆21Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- MMD and Relative MMD test☆31Updated 9 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆32Updated 8 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆126Updated 6 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Lua implementation of Entropy-SGD☆81Updated 7 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago