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

deepwalk kernel-methods attention-mechanism network-embedding graph-kernel graph-kernels graph-convolutional-networks classification-algorithm node2vec weisfeiler-lehman graph-embedding graph-classification graph-attention-networks graph-representation-learning graph2vec deep-graph-kernels netlsd graph-attention-model structural-attention node-embedding

• Updated Mar 18, 2023
• Python

Learning kernels to maximize the power of MMD tests

python machine-learning theano tensorflow generative-adversarial-network statistical-tests kernel-methods hypothesis-testing maximum-mean-discrepancy shogun

• Updated Jan 11, 2018
• Python

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

kernel deep-learning paper regression uncertainty bayesian-methods classification kernel-methods one-shot-learning uncertainty-quantification gaussian-processes kernels meta-learning shot-learning deep-kernel-learning few-shot-learning gpytorch

• Updated Jan 19, 2022
• Python

Large-scale, multi-GPU capable, kernel solver

python machine-learning ai kernel pytorch kernel-methods large-scale-learning

• Updated Oct 14, 2026
• Python

Scala Library/REPL for Machine Learning Research

machine-learning scala tensorflow repl machine-learning-algorithms regression classification machine-learning-api scala-library kernel-methods committee-models gaussian-processes

• Updated Apr 21, 2023
• Scala

Fast and memory-efficient radial basis function (RBF) interpolation

python cpp interpolation regression surface-reconstruction smoothing splines spline kernel-methods geostatistics kriging surface-modeling radial-basis-function rbf

• Updated Oct 6, 2026
• C++

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

data-science machine-learning neural-network forecasting autoencoder dynamical-systems kernel-methods conservation-laws autoencoders sindy dynamic-mode-decomposition time-delay stroboscopic-map poincare-map autoencoder-neural-network extended-dynamic-mode-decomposition physics-informed-learning sindy-algorithm physics-informed-neural-networks universal-approximation-theorem

• Updated Oct 28, 2025
• Jupyter Notebook

A package for Multiple Kernel Learning in Python

kernel-methods representation-learning mkl string-kernel multiple-kernel-learning boolean-kernel

• Updated Apr 3, 2023
• Python

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

machine-learning paths pattern-recognition kernel-methods chemoinformatics graph-kernels graph-edit-distance walks graph-representations pre-image

• Updated Jun 7, 2025
• Jupyter Notebook

ML4Chem: Machine Learning for Chemistry and Materials

machine-learning kernel chemistry physics deeplearning kernel-methods materials-science

• Updated Dec 9, 2024
• Python

A Matlab benchmarking toolbox for kernel adaptive filtering

signal-processing matlab kernel-methods kernel-adaptive-filtering

• Updated May 5, 2023
• MATLAB

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

astronomy visualisation astrophysics plotting kernel-methods smoothed-particle-hydrodynamics fits interpolation-methods

• Updated Oct 27, 2026
• Fortran

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

python deep-learning remote-sensing convolutional-neural-networks kernel-methods unsupervised-learning kpca change-detection kpca-convolution vhr-images

• Updated Jan 31, 2024
• Python

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

machine-learning kernel-methods gaussian-processes extrapolation

• Updated Jul 10, 2018
• Python

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

python machine-learning statistical-tests kernel-methods goodness-of-fit

• Updated Jul 11, 2019
• Python

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

python machine-learning statistical-tests kernel-methods

• Updated May 13, 2018
• OpenEdge ABL

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

machine-learning signal-processing jupyter-notebook filters kernel-methods adaptive-filters kernel-filters

• Updated Aug 2, 2019
• Jupyter Notebook

Kernel Methods Toolbox for Matlab/Octave

signal-processing matlab kernel-methods

• Updated Jun 14, 2019
• MATLAB

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

windows kernel-module executable x86 arm-templates kernel-methods arm64 exploitation-framework windows-exploitation x86-kernel windows-security cybersecurity-search-engine

• Updated Jan 6, 2024

machine-learning kernel-methods clustering-algorithm online-learning kernel-functions batch-learning tree-kernel

• Updated Oct 30, 2021
• Java