robertnishihara / gessLinks
An MCMC algorithm for sampling continuous probability distributions in parallel
☆19Updated 10 years ago
Alternatives and similar repositories for gess
Users that are interested in gess are comparing it to the libraries listed below
Sorting:
- Python package for inference with Gaussian processes☆11Updated 10 years ago
- ☆99Updated 7 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆26Updated 7 years ago
- Generate stochastic processes using Python. Unfortunately not maintained any longer =(☆112Updated 10 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Likelihood-free inference toolbox.☆56Updated 8 years ago
- Variational Fourier Features☆87Updated 4 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆84Updated last year
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- Backpropagate derivatives through the Cholesky decomposition☆59Updated 5 years ago
- A Gaussian process toolbox in python☆42Updated 13 years ago
- Kernel structure discovery research code - likely to be unstable☆195Updated 10 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- A probabilistic programming framework based on TensorFlow☆88Updated 6 years ago
- Code for AutoGP☆27Updated 6 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆85Updated 5 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆67Updated 8 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 9 years ago
- Bayesian dessert for Lasagne☆83Updated 8 years ago
- Implementation of an algorithm for Markov chain Monte Carlo with data subsampling☆32Updated 9 years ago
- Clustering time series using Gaussian processes and Variational Bayes.☆39Updated 5 years ago
- Ordered Weighted L1 regularization for classification and regression in Python☆52Updated 7 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆46Updated 10 years ago
- Collection of jupyter notebooks for demonstrating software.☆167Updated 2 years ago
- ELFI - Engine for Likelihood-Free Inference☆280Updated 8 months ago
- Particle Gibbs for Bayesian Additive Regression Trees☆33Updated 10 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆109Updated 7 years ago
- Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data☆25Updated 9 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago