ericsuh / dirichletLinks
Dirichlet MLE python library
☆117Updated 3 weeks ago
Alternatives and similar repositories for dirichlet
Users that are interested in dirichlet are comparing it to the libraries listed below
Sorting:
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 5 years ago
- Bayesian nonparametric machine learning for Python☆228Updated 2 years ago
- ☆155Updated 5 years ago
- Scikit-learn compatible estimation of general graphical models☆247Updated 2 months ago
- Variational Fourier Features☆85Updated 4 years ago
- ☆98Updated 7 years ago
- NumPy implementation of infinite latent feature model (aka Indian Buffet Process or IBP)☆49Updated 7 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated last year
- Dependent multinomials made easy: stick-breaking with the Pólya-gamma augmentation☆61Updated 4 years ago
- ELFI - Engine for Likelihood-Free Inference☆277Updated 3 months ago
- Introduction to Nonparametric Bayes, Infinite Mixture Models, and the Dirichlet Process (+ McDonald's)☆306Updated 10 years ago
- Automated Scalable Bayesian Inference☆131Updated 3 years ago
- some tools for gaussian linear dynamical systems☆89Updated 7 years ago
- Kernel structure discovery research code - likely to be unstable☆191Updated 10 years ago
- Collection of jupyter notebooks for demonstrating software.☆169Updated 2 years ago
- General Latent Feature Modeling for Heterogeneous data☆49Updated last year
- Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave☆77Updated last year
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Collapsed Variational Bayes☆72Updated 5 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated last year
- Python software for selective inference☆52Updated 2 years ago
- megaman: Manifold Learning for Millions of Points☆328Updated 2 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated last year
- ☆239Updated 8 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago
- python code for kernel methods☆40Updated 6 years ago
- Bayesian or-of-and☆35Updated 3 years ago