kamperh / bayes_gmm
Bayesian Gaussian mixture models in Python.
☆62Updated last year
Related projects: ⓘ
- Deep Gaussian Processes in matlab☆90Updated 3 years ago
- Variational Inference in Gaussian Mixture Model☆58Updated 3 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 10 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆31Updated 7 years ago
- Sticky hierarchical Dirichlet process hidden Markov model for time series denoising☆44Updated 8 years ago
- ☆28Updated 5 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…☆77Updated 6 years ago
- Multi-task Gaussian Process☆43Updated 9 years ago
- Variational Gaussian Process State-Space Models☆21Updated 8 years ago
- Heterogeneous Multi-output Gaussian Processes☆52Updated 4 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆65Updated 7 years ago
- Multiple output Gaussian processes in MATLAB including the latent force model.☆48Updated 8 years ago
- Variational Dirichlet Process Gaussian Mixture Models☆27Updated 9 years ago
- Streaming sparse Gaussian process approximations☆62Updated last year
- Deep Gaussian Processes in Python☆230Updated 3 years ago
- Neural Processes implementation for 1D regression☆65Updated 5 years ago
- Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'☆22Updated 10 years ago
- Kalman Variational Auto-Encoder☆133Updated 5 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆32Updated 10 years ago
- Variational Fourier Features☆81Updated 3 years ago
- State space modeling with recurrent neural networks☆42Updated 6 years ago
- Matlab implementations of Gaussian processes and other machine learning tools.☆132Updated 7 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 6 years ago
- ☆46Updated last year
- Convolutional Gaussian processes based on GPflow.☆95Updated 6 years ago
- A collection of Gaussian process models☆29Updated 7 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆36Updated 7 years ago
- Code for density estimation with nonparametric cluster shapes.☆38Updated 8 years ago
- Python code for Expectation-Maximization estimate of Gaussian mixture model☆74Updated 5 years ago