likang7 / variational-dpgmmLinks
Variational Dirichlet Process Gaussian Mixture Models
☆29Updated 10 years ago
Alternatives and similar repositories for variational-dpgmm
Users that are interested in variational-dpgmm are comparing it to the libraries listed below
Sorting:
- Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)☆13Updated 6 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆35Updated 11 years ago
- Direct Gibbs sampling for DPMM using python.☆16Updated 8 years ago
- The source code is related to our work- Shreyas Seshadri, Ulpu Remes and Okko Rasanen: "Dirichlet process mixture models for clustering i…☆10Updated 7 years ago
- Variational Inference in Gaussian Mixture Model☆59Updated 4 years ago
- Dirichlet process mixture model code in Matlab. Sampling and variational.☆71Updated 12 years ago
- ☆28Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Multi-task Gaussian Process☆43Updated 10 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 7 months ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Matlab Code for Variational Gaussian Copula Inference☆16Updated 9 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 7 years ago
- ☆46Updated 2 years ago
- Bayesian Gaussian mixture models in Python.☆63Updated 2 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated 2 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- ☆25Updated 6 years ago
- Generic implementation of GP model☆8Updated 6 years ago
- Streaming sparse Gaussian process approximations☆66Updated 2 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 2 years ago
- PyTorch implementation of the Covariate-GPLVM☆26Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processes☆18Updated 9 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago