lucidfrontier45 / PyVB
Python implementation for Variational Bayesian Learning
☆13Updated 11 years ago
Alternatives and similar repositories for PyVB:
Users that are interested in PyVB are comparing it to the libraries listed below
- Open access book on variational Bayesian methods written collaboratively☆28Updated 9 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago
- Repo for a paper about constructing priors on very deep models.☆72Updated 8 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 10 years ago
- ☆40Updated 5 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆65Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 8 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Deep Gaussian Processes in matlab☆91Updated 3 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 9 years ago
- Code for density estimation with nonparametric cluster shapes.☆38Updated 8 years ago
- Stochastic Gradient MCMC algorithms implemented in theano (and autograd)☆10Updated 8 years ago
- Variational Sparse Spectrum Gaussian Process toolkit☆22Updated 9 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Bayesian GPLVM in MATLAB and R☆74Updated 7 years ago
- Sampling via Moment Sharing☆11Updated 9 years ago
- Bayesian Gaussian mixture models in Python.☆64Updated last year
- State space modeling with recurrent neural networks☆43Updated 6 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆47Updated 9 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 6 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆33Updated 11 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 6 years ago
- Variational Fourier Features☆83Updated 3 years ago
- Python library for working with gaussian processes☆14Updated 11 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Preconditioning Kernel Matrices☆15Updated 8 years ago