kernel-methods
There are 246 repositories under kernel-methods topic.
benedekrozemberczki/awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
djsutherland/opt-mmd
Learning kernels to maximize the power of MMD tests
tailhq/DynaML
Scala Library/REPL for Machine Learning Research
BayesWatch/deep-kernel-transfer
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
FalkonML/falkon
Large-scale, multi-GPU capable, kernel solver
polatory/polatory
Fast radial basis function interpolation for large scale data
IvanoLauriola/MKLpy
A package for Multiple Kernel Learning in Python
jajupmochi/graphkit-learn
A python package for graph kernels, graph edit distances, and graph pre-image problem.
muammar/ml4chem
ML4Chem: Machine Learning for Chemistry and Materials
steven2358/kafbox
A Matlab benchmarking toolbox for kernel adaptive filtering
ssydasheng/Neural-Kernel-Network
Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
jbramburger/DataDrivenDynSyst
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
wittawatj/kernel-gof
NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
wittawatj/interpretable-test
NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
ChenHongruixuan/KPCAMNet
[IEEE TCYB 2021] Official Python implementation for Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network
danieljprice/splash
SPLASH is an interactive visualisation and plotting tool using kernel interpolation, mainly used for Smoothed Particle Hydrodynamics simulations
ninja3697/Kernel-Adaptive-Filtering-in-Python
Implementation of LMS, RLS, KLMS and KRLS filters in Python
steven2358/kmbox
Kernel Methods Toolbox for Matlab/Octave
DSPKM/DSPKM
This is the page for the book Digital Signal Processing with Kernel Methods.
annamalai-nr/subgraph2vec_gensim
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"
sigvaldm/localreg
Multivariate Local Polynomial Regression and Radial Basis Function Regression
dnbaker/frp
FRP: Fast Random Projections
raamana/kernelmethods
Foundational library for Kernel methods in pattern analysis and machine learning
TheDatumOrg/grail-python
"GRAIL: Efficient Time-Series Representation Learning"
qiskit-community/prototype-quantum-kernel-training
Toolkit for training quantum kernels in machine learning applications
activatedgeek/svgd
PyTorch implementation of Stein Variational Gradient Descent
glitteru/CodMWKernelInjector
Undetected Call of duty: MW, Warzone kernel injector.
jkfitzsimons/IPyNotebook_MachineLearning
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
paulveillard/cybersecurity-windows-exploitation
A collection of awesome software, libraries, learning tutorials, documents and books, awesome resources and cool stuff about ARM and Windows Exploitation.
annamalai-nr/subgraph2vec_tf
This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper
wittawatj/cadgan
ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
392781/scikit-ntk
Neural Tangent Kernel (NTK) module for the scikit-learn library
antoine-moulin/MVA
Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.
lightonai/supervised-random-projections
Python implementation of supervised PCA, supervised random projections, and their kernel counterparts.
operalib/operalib
Learning with operator-valued kernels