mcdickenson / em-gaussian
Python code for Expectation-Maximization estimate of Gaussian mixture model
☆76Updated 6 years ago
Alternatives and similar repositories for em-gaussian:
Users that are interested in em-gaussian are comparing it to the libraries listed below
- Bayesian Gaussian mixture models in Python.☆64Updated last year
- Variational Inference in Gaussian Mixture Model☆59Updated 4 years ago
- Probabilistic Principal Component Analysis☆61Updated 7 years ago
- ☆38Updated 8 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆66Updated 7 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 5 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2017☆26Updated 2 years ago
- Collection of probabilistic models and inference algorithms☆241Updated 4 years ago
- Matlab code for the introduction to Gaussian processes, 2008☆30Updated 9 years ago
- Deep Gaussian Processes in matlab☆91Updated 3 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated 8 months ago
- State space modeling with recurrent neural networks☆43Updated 6 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Updated 9 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.☆57Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Deep Gaussian Processes in Python☆233Updated 3 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated 7 months ago
- ☆28Updated 6 years ago
- Kernel Methods Toolbox for Matlab/Octave☆51Updated 5 years ago
- A simple MCMC framework for training Gaussian processes adding functionality to GPy.☆21Updated 10 years ago
- Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.☆104Updated 12 years ago
- Bayesian Weight Uncertainty Dense Layer for Keras☆48Updated 8 years ago
- Bayesian nonparametric machine learning for Python☆216Updated last year
- An exploration of mixture density networks☆33Updated 7 years ago