Variational inference for Dirichlet process mixture models with multinomial mixture components.
☆37Jan 15, 2014Updated 12 years ago
Alternatives and similar repositories for dpmm
Users that are interested in dpmm are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Variational Dirichlet Process Gaussian Mixture Models☆29Feb 2, 2015Updated 11 years ago
- Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)☆13Oct 8, 2018Updated 7 years ago
- Dirichlet process mixture model code in Matlab. Sampling and variational.☆72Nov 4, 2012Updated 13 years ago
- ☆11Mar 9, 2018Updated 8 years ago
- Dirichlet process mixture model (DPMM) for datamicroscopes☆14Oct 9, 2015Updated 10 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Jun 20, 2014Updated 12 years ago
- Direct Gibbs sampling for DPMM using python.☆17Jun 2, 2017Updated 9 years ago
- Efficient Dirichlet process clustering☆26Jun 22, 2013Updated 13 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆44May 18, 2017Updated 9 years ago
- Implementation of Deep Dirichlet Multinomial Regression in python + cython.☆16Mar 7, 2018Updated 8 years ago
- A collection of Black Box Variational Inference algorithms implemented in an object-oriented Python framework using Autograd.☆11Sep 7, 2018Updated 8 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Apr 16, 2015Updated 11 years ago
- Deep Generative Models with Stick-Breaking Priors☆95May 23, 2016Updated 10 years ago
- A pytorch version of hamiltonian monte carlo☆14Jun 26, 2019Updated 7 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Multi-output Gaussian process regression via multi-task neural network☆13Dec 3, 2019Updated 6 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Jan 2, 2021Updated 5 years ago
- Non-parametric Bayesian in Python, including Indian buffet process (IBP), hierarchical Dirichlet process (HDP).☆73Sep 25, 2015Updated 11 years ago
- Matlab Code for Variational Gaussian Copula Inference☆18Mar 15, 2016Updated 10 years ago
- Python code for HDP(Hierarchical Dirichlet Process) using Direct Assignment☆20Feb 9, 2017Updated 9 years ago
- Gaussian Process Prior Variational Autoencoder☆86Nov 28, 2018Updated 7 years ago
- Python implementation for Variational Bayesian Learning☆13Jan 23, 2014Updated 12 years ago
- ☆12Dec 8, 2022Updated 3 years ago
- Java implementation of Dirichlet Process Mixture Model.☆20Jul 7, 2014Updated 12 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Variational Bayesian Mixture of Factor Analysers☆24Jan 24, 2015Updated 11 years ago
- Collapsed Variational Bayes☆72Sep 27, 2019Updated 6 years ago
- Evaluating Durability: Benchmark Insights into Multimodal Watermarking☆12Jun 7, 2024Updated 2 years ago
- Nonparametric Topic Modeling with Word Vectors☆75May 20, 2017Updated 9 years ago
- General Bayesian non-parametric hidden Markov model☆19Oct 17, 2013Updated 12 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Nov 29, 2022Updated 3 years ago
- ☆12Apr 20, 2023Updated 3 years ago
- Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models implemented by pytorch☆13Jun 11, 2018Updated 8 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Apr 25, 2017Updated 9 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders☆216Mar 4, 2020Updated 6 years ago
- Categorical Latent Gaussian Process☆16Mar 7, 2015Updated 11 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Dec 8, 2022Updated 3 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10May 16, 2018Updated 8 years ago
- Train and visualise a latent variable model of moving objects.☆16Apr 28, 2020Updated 6 years ago
- ☆11Jun 17, 2016Updated 10 years ago
- Sticky hierarchical Dirichlet process hidden Markov model for time series denoising☆50Aug 28, 2016Updated 10 years ago