YohanJung

abocpd_matlab

Online-Kernel-Learning

This is all the codes used in "Large Scale Online Kernel Learning"

online_FM

RRF

Reparameterized Random Features

vhmm_matlab

agp

Automated Variational Inference for Gaussian Process Models

boundary-gp

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

DPMM

Dirichlet process mixture model code in Matlab. Sampling and variational.

geepee

A collection of Gaussian process models

GPCnoise

Implementation of scalable Gaussian process classification (GPC) with additive noise for various likelihoods

GPML

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

IBP

Indian Buffet Process; Variational Inference

InfiGMM

Infinite Gaussian Mixture Model / Variational EM

MGPC_Release

Source code for https://www.ijcai.org/proceedings/2017/642

normalizing-flows-tutorial

Tutorial on normalizing flows.

nssm-gp

Non-stationary spectral mixture kernels implemented in GPflow

pyhsmm

RandMatrixMatlab

simple MATLAB code for randomized matrix computation

revrand

A library of scalable Bayesian generalised linear models with fancy features

SFTRL

Code for "Sketched Follow-The-Regularized-Leader for Online Factorization Machine

srf

Random Fourier Features

ssdkl

Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

YohanJung.github.io

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