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kernel-methods

Here are 175 public repositories matching this topic...

awesome-graph-classification

benedekrozemberczki / awesome-graph-classification

Sponsor

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 2, 2022
Python

tailhq / DynaML

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 15, 2021
Scala

djsutherland / opt-mmd

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

BayesWatch / deep-kernel-transfer

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

FalkonML / falkon

Large-scale, multi-GPU capable, kernel solver

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

Updated Jul 29, 2022
Python

IvanoLauriola / MKLpy

A package for Multiple Kernel Learning in Python

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

Updated Feb 3, 2022
Python

jajupmochi / graphkit-learn

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 24, 2022
Jupyter Notebook

muammar / ml4chem

ML4Chem: Machine Learning for Chemistry and Materials

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

Updated Apr 9, 2022
Python

steven2358 / kafbox

A Matlab benchmarking toolbox for kernel adaptive filtering

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

Updated May 12, 2021
MATLAB

ssydasheng / Neural-Kernel-Network

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

wittawatj / kernel-gof

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

wittawatj / interpretable-test

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

python machine-learning statistical-tests kernel-methods

Updated May 13, 2018
OpenEdge ABL

SAG-KeLP / kelp-full

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

Updated Oct 30, 2021
Java

steven2358 / kmbox

Kernel Methods Toolbox for Matlab/Octave

signal-processing matlab kernel-methods

Updated Jun 14, 2019
MATLAB

raamana / kernelmethods

Foundational library for Kernel methods in pattern analysis and machine learning

data-science machine-learning kernel svm scikit-learn data-structures pattern-analysis pattern-recognition metric-learning kernel-methods kernels mkl kernel-functions multiple-kernel-learning

Updated Sep 5, 2021
Python

MLDroid / 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"

deep-learning word2vec gensim kernel-methods graph-kernels

Updated Apr 29, 2017
Python

dnbaker / frp

FRP: Fast Random Projections

indexing simd kernel-methods fftw3-binding fht orthogonal-random-projections jl-transform dy dynamic-continuous-indexing

Updated Jun 1, 2020
C++

ChenHongruixuan / KPCAMNet

[TCYB 2021] Official Python implementation for 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 Feb 22, 2022
Python

DSPKM / DSPKM

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

machine-learning svm kernel-methods digital-signal-processing support-vector-machines

Updated Jun 22, 2017
MATLAB

danieljprice / splash

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 Jul 25, 2022
Fortran

ninja3697 / Kernel-Adaptive-Filtering-in-Python

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

jkfitzsimons / IPyNotebook_MachineLearning

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

machine-learning ipython-notebook bayesian-inference kernel-methods gaussian-processes bayesian-machine-learning

Updated Jul 27, 2015

MLDroid / subgraph2vec_tf

This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper

deep-neural-networks deep-learning tensorflow kernel-methods kdd skipgram graph-kernels

Updated Oct 13, 2017
Python

activatedgeek / svgd

PyTorch implementation of Stein Variational Gradient Descent

bayesian bayesian-inference kernel-methods non-parametric-inference stein-variational-gradient-decent

Updated Apr 9, 2019
Jupyter Notebook

wittawatj / cadgan

ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.

machine-learning generative-adversarial-network generative-model kernel-methods

Updated Jun 30, 2020
Python

sigvaldm / localreg

Open

Return polyfit coefficients (or SymPy expression)

sigvaldm commented Sep 6, 2021

Today polyfit() doesn't return fitting coefficient like NumPy's does, but NumPy's is only 1D. Now that localreg is multivariate, it would be nice to make it more similar to NumPy's for replacement. The ordering of the coefficients are more complicated for the multivariate case, but perhaps there could also be a class or something that could return a SymPy expression of the fit?

Read more

enhancement good first issue

Open

KDE

lightonai / supervised-random-projections

Python implementation of supervised PCA, supervised random projections, and their kernel counterparts.

randomization pca kernel-methods machine-leanring

Updated May 4, 2020
Python

wittawatj / kernel-mod

NeurIPS 2018. Linear-time model comparison tests.

machine-learning kernel-methods hypothesis-testing interpretability model-comparison

Updated Feb 15, 2020
Jupyter Notebook

qiskit-community / prototype-quantum-kernel-training

Toolkit for training quantum kernels in machine learning applications

machine-learning prototype quantum-computing kernel-methods qiskit

Updated Jun 3, 2022
Python

djsutherland / igms

Implicit generative models and related stuff based on the MMD, in PyTorch

python machine-learning pytorch statistical-tests kernel-methods hypothesis-testing maximum-mean-discrepancy generative-models

Updated Sep 24, 2020
Jupyter Notebook

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