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autogp

Code for AutoGP

cogp

Collaborative multi-output Gaussian processes

convolutional_deep_gp_random_features

Implementation of paper Calibrating Deep Convolutional Gaussian Processes

deep-kernel-learning-for-one-class-classification

Minimum Variance-Embedded Deep Kernel Regularized Least Square Method for One-class Classification and Its Applications to Biomedical Data

deep-rff-pytorch

deep_gp_random_features

deepcgp

Deep convolutional gaussian processes.

deepgp_approxep

see https://github.com/thangbui/geepee for a faster implementation

deepmkl

Deep Multiple Kernel Learning by Span Bound

dk-former

doubly-stochastic-dgp

Deep Gaussian Processes with Doubly Stochastic Variational Inference

ebonilla.github.io

Edwin V. Bonilla's Personal Web Page

gaussianprocesses

Modern Gaussian Processes: Scalable Inference and Novel Applications

gppe

Gaussian Process Elicitation Framework

image-folder

keras-gp

Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.

learn-python3

Learn Python 3 Sample Code

learngit

learnssh

linearizedgp

Gaussian processes with general nonlinear likelihoods using the unscented transform or Taylor series linearisation.

models

Models built with TensorFlow

mtgp

Multi-task Gaussian Process

nips2014poster

NIPS 2014 Poster on "extended and unscented Gaussian Processes"

nips2014poster-1

Poster on Automated Variational Inference

nngp

Deep neural network kernel for Gaussian process

prml

PRML algorithms implemented in Python

random-feature-maps

Fast Random Kernelized Features: Support Vector Machine Classification for High-Dimensional IDC Dataset

random-fourier-features

Implementation of random fourier features for support vector machine

region-adjacency

rff_pytorch