kamperh / bayes_gmmLinks
Bayesian Gaussian mixture models in Python.
☆63Updated 2 years ago
Alternatives and similar repositories for bayes_gmm
Users that are interested in bayes_gmm are comparing it to the libraries listed below
Sorting:
- Deep Gaussian Processes in matlab☆93Updated 3 years ago
- Variational Inference in Gaussian Mixture Model☆59Updated 4 years ago
- Deep Gaussian Processes in Python☆234Updated 4 years ago
- ☆28Updated 6 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆33Updated 8 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Deep Markov Models☆132Updated 6 years ago
- Sticky hierarchical Dirichlet process hidden Markov model for time series denoising☆48Updated 8 years ago
- Kalman Variational Auto-Encoder☆136Updated 6 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…☆78Updated 7 years ago
- ☆46Updated 2 years ago
- State space modeling with recurrent neural networks☆45Updated 7 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Matlab implementations of Gaussian processes and other machine learning tools.☆140Updated 8 years ago
- Online Robust Principal Component Analysis☆95Updated 5 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆185Updated 11 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆40Updated 6 years ago
- Multiple output Gaussian processes in MATLAB including the latent force model.☆51Updated 9 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Clean repo for tensor-train RNN implemented in TensorFlow☆68Updated 5 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆404Updated last year
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.☆216Updated 6 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 7 years ago