A collection of important graph embedding, classification and representation learning papers with implementations.

Learning kernels to maximize the power of MMD tests

Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

Scala Library/REPL for Machine Learning Research

Large-scale, multi-GPU capable, kernel solver

Fast radial basis function interpolation and kriging for large scale data

Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

A package for Multiple Kernel Learning in Python

A python package for graph kernels, graph edit distances, and graph pre-image problem.

ML4Chem: Machine Learning for Chemistry and Materials

A Matlab benchmarking toolbox for kernel adaptive filtering

[IEEE TCYB 2022] Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network

Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326

NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.

SPLASH is an interactive visualisation and plotting tool using kernel interpolation, mainly used for Smoothed Particle Hydrodynamics simulations

NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.

Kernel Methods Toolbox for Matlab/Octave

No description provided.

Implementation of LMS, RLS, KLMS and KRLS filters in Python

A collection of awesome software, libraries, learning tutorials, documents and books, awesome resources and cool stuff about ARM and Windows Exploitation.

Multivariate Local Polynomial Regression and Radial Basis Function Regression

PyTorch implementation of Stein Variational Gradient Descent

This is the page for the book Digital Signal Processing with Kernel Methods.

Toolkit for training quantum kernels in machine learning applications

FRP: Fast Random Projections

Foundational library for Kernel methods in pattern analysis and machine learning

Contains the code (and working vm setup) for our KDD MLG 2016 paper titled: "subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs"

"GRAIL: Efficient Time-Series Representation Learning"

Undetected Call of duty: MW, Warzone kernel injector.

Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation