trevorcampbell / sda-bnp
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
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆33Updated 11 years ago
- ☆22Updated last year
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 9 years ago
- ☆11Updated 8 years ago
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- Wasserstein regularization for sparse multi-task regression☆15Updated 4 years ago
- Software relating to relational empirical risk minimization☆17Updated 3 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 10 years ago
- Sampling via Moment Sharing☆11Updated 9 years ago
- Movies Recommendation with Hierarchical Poisson Factorization in Edward☆18Updated 7 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated last year
- Structure learning for sparse graphs with latent variables☆45Updated 8 years ago
- Dirichlet Process K-means☆47Updated 8 months ago
- Code to reproduce all the results in the paper: "Learning dynamics of linear denoising autoencoders." (ICML 2018)☆12Updated 6 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Python package to sample from determinantal point processes☆18Updated 9 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton☆24Updated 8 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Variational Information Maximization for Feature Selection☆11Updated 8 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Variational inference for Gaussian mixture models☆34Updated 11 years ago
- Implementation of Sum-Product Attend-Infer-Repeat☆30Updated 4 years ago
- ☆11Updated last year
- Code for "Boosted Generative Models", AAAI 2018.☆20Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 8 years ago
- Dirichlet process mixture model code in Matlab. Sampling and variational.☆71Updated 12 years ago