jhamrick / gaussian_processes
Python library for working with gaussian processes
☆14Updated 10 years ago
Related projects ⓘ
Alternatives and complementary repositories for gaussian_processes
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 10 years ago
- Variational Fourier Features☆83Updated 3 years ago
- Code for AutoGP☆26Updated 5 years ago
- ☆40Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Collaborative filtering with the GP-LVM☆25Updated 9 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆48Updated 8 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 10 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆31Updated 8 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 5 years ago
- Code for density estimation with nonparametric cluster shapes.☆38Updated 8 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 10 years ago
- Variational Sparse Spectrum Gaussian Process toolkit☆22Updated 9 years ago
- Gaussian Process Random Fields☆21Updated 9 years ago
- Neural Processes implementation for 1D regression☆65Updated 5 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 7 years ago
- Python package for inference with Gaussian processes☆11Updated 9 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆24Updated 6 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆68Updated 10 years ago
- code for stochastic expectation propagation☆16Updated 9 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Repo for a paper about constructing priors on very deep models.☆70Updated 8 years ago
- my PhD thesis on Bayesian inference☆28Updated 11 years ago
- Parameterization Framework for parameterized model creation and handling.☆47Updated 10 months ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 7 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 4 years ago