trevorcampbell / sda-bnpLinks
Streaming, Distributed, Asynchronous Bayesian Nonparametric Inference
☆12Updated 9 years ago
Alternatives and similar repositories for sda-bnp
Users that are interested in sda-bnp are comparing it to the libraries listed below
Sorting:
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 10 years ago
- Deep Generative Models with Stick-Breaking Priors☆96Updated 9 years ago
- Dirichlet process mixture model code in Matlab. Sampling and variational.☆71Updated 12 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 9 years ago
- Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017☆36Updated 6 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton☆25Updated 9 years ago
- This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…☆41Updated 11 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆35Updated 11 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 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"☆103Updated 9 years ago
- Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)☆20Updated 7 years ago
- ☆11Updated 9 years ago
- ☆11Updated 7 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 11 months ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆69Updated 8 years ago
- ☆12Updated 2 years ago
- Dirichlet Process K-means☆48Updated last year
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- Poisson-Gamma dynamical systems☆17Updated 8 years ago
- Wasserstein regularization for sparse multi-task regression☆15Updated 5 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Updated 8 years ago
- Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'☆22Updated 11 years ago
- Black Box Variational Inference☆14Updated 10 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Variational Dirichlet Process Gaussian Mixture Models☆29Updated 10 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago