likang7 / variational-dpgmm
Variational Dirichlet Process Gaussian Mixture Models
β29Updated 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
- Variational inference for Dirichlet process mixture models with multinomial mixture components.β33Updated 11 years ago
- Variational Gaussian Process State-Space Modelsβ23Updated 9 years ago
- π€Ώ Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0β27Updated last year
- Python implementation of the PR-SSM.β51Updated 6 years ago
- Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)β13Updated 6 years ago
- β28Updated 6 years ago
- The source code is related to our work- Shreyas Seshadri, Ulpu Remes and Okko Rasanen: "Dirichlet process mixture models for clustering iβ¦β10Updated 7 years ago
- Direct Gibbs sampling for DPMM using python.β16Updated 7 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.β43Updated 11 years ago
- Streaming sparse Gaussian process approximationsβ64Updated 2 years ago
- Matlab Code for Variational Gaussian Copula Inferenceβ16Updated 9 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019β41Updated 2 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code forβ¦β17Updated 6 years ago
- Variational Inference in Gaussian Mixture Modelβ59Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)β48Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementationβ37Updated 7 years ago
- Dirichlet process mixture model code in Matlab. Sampling and variational.β71Updated 12 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)β83Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)β65Updated 5 years ago
- Heterogeneous Multi-output Gaussian Processesβ52Updated 4 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variablesβ13Updated 7 years ago
- Additive Gaussian Process Bandits - version 1.0β27Updated 8 years ago
- β40Updated 5 years ago
- Deep Gaussian Processes in matlabβ92Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inferenceβ38Updated 5 years ago
- Multiple output Gaussian processes in MATLAB including the latent force model.β49Updated 9 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwoβ¦β54Updated 6 months ago
- Implementation of learning a Gaussian mixture model using tensor decomposition.β16Updated 7 years ago
- Asymmetric Transfer Learning with Deep Gaussian Processesβ18Updated 9 years ago
- Kalman Variational Auto-Encoderβ135Updated 6 years ago