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63 search results found

Awesome Graph Classification ⭐ 4,703

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

Opt Mmd ⭐ 204

Learning kernels to maximize the power of MMD tests

Scala Library/REPL for Machine Learning Research

Large-scale, multi-GPU capable, kernel solver

Deep Kernel Transfer ⭐ 142

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

Polatory ⭐ 133

Fast, memory-efficient 3D spline interpolation and global kriging, via RBF (radial basis function) interpolation.

A package for Multiple Kernel Learning in Python

Graphkit Learn ⭐ 107

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

A Matlab benchmarking toolbox for kernel adaptive filtering

ML4Chem: Machine Learning for Chemistry and Materials

Neural Kernel Network ⭐ 62

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

Kpcamnet ⭐ 57

[IEEE TCYB 2021] Official Python implementation for Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network

Kernel Gof ⭐ 56

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

Kelp Full ⭐ 53

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

Interpretable Test ⭐ 44

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

Kernelmethods ⭐ 42

Foundational library for Kernel methods in pattern analysis and machine learning

Datadrivendynsyst ⭐ 40

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

Subgraph2vec_gensim ⭐ 36

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"

Kernel Methods Toolbox for Matlab/Octave

Prototype Quantum Kernel Training ⭐ 31

Toolkit for training quantum kernels in machine learning applications

FRP: Fast Random Projections

Localreg ⭐ 26

Multivariate Local Polynomial Regression and Radial Basis Function Regression

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

Subgraph2vec_tf ⭐ 21

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

Supervised Random Projections ⭐ 18

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

Kernel Mod ⭐ 18

NeurIPS 2018. Linear-time model comparison tests.

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

Operalib ⭐ 17

Learning with operator-valued kernels

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

Kernelknn ⭐ 15

Kernel k Nearest Neighbors in R

Fsic Test ⭐ 15

ICML 2017. Kernel-based adaptive linear-time independence test.

Cybersecurity Windows Exploitation ⭐ 15

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

Covariancefunctions.jl ⭐ 15

Lazy, structured, and efficient operations with kernel matrices.

Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.

Machine Learning Summer Schools ⭐ 14

Curated materials for different machine learning related summer schools

Mmdagg Paper ⭐ 14

Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.15073

Kernel Ep ⭐ 14

UAI 2015. Kernel-based just-in-time learning for expectation propagation

Kelp Input Generator ⭐ 13

Utility project to generate KeLP compliant representations

A lightweight didactic library of kernel methods using the back-end JAX.

Archived repo (see Readme) - R package for regression and discrimination, with special focus on chemometrics and high-dimensional data.

Nystrompca ⭐ 11

Efficient non-linear PCA through kernel PCA with the Nyström method

Quadrature-based features for kernel approximation

Scikit Ntk ⭐ 11

Neural Tangent Kernel (NTK) module for the scikit-learn library

Multi Kernel Linear Mixed Models for Complex Phenotype Prediction

Kernel Localized Linear Regression (KLLR)

Manifoldem_python ⭐ 8

ManifoldEM Python suite

Dimensionality Reduction via Regression using Kernel Ridge Regression in R

Kpca Denoising Python ⭐ 8

Reproduction of the experiments presented in Kernel PCA and De-noising in Feature Spaces, as a project in DD2434 Machine Learning Advance Course during Winter 2016

Deterministicparticleflowcontrol ⭐ 8

Repository for Deterministic Particle Flow Control framework

Hotstepper ⭐ 7

A Numpy based step function library for analysis and profit. More than just taking you up and down.

AISTATS 2016. K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.

Regularization_for_machine_learning ⭐ 6

Regularization for Machine Learning-RegML GUI

Automatic_design_of_quantum_feature_maps_genetic_auto Generation ⭐ 6

Registered Software. Official code of the published article "Automatic design of quantum feature maps". This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for tabular data.

Multiplekernel Leastsquares Supportvectormachine ⭐ 6

Multiple Kernel Least Squares Suport Vector Machine provide classification model.

Ksdagg Paper ⭐ 6

Code for reproducible experiments presented in KSD Aggregated Goodness-of-fit Test. https://arxiv.org/abs/2202.00824 NeurIPS 2022

Chbmit Seizure Prediction ⭐ 5

Anomaly prediction using brain signals with Fourier transformed features and SVM classifier.

Kernel Adaptive Filtering In Python ⭐ 5

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

Kernel Matrix Benchmarks ⭐ 5

Benchmark of kernel matrix-vector products and inversions (regression, system resolution).

Recursive Nystrom ⭐ 5

Python implementation of RLS-Nystrom

MMD-FUSE package implementing the MMD-FUSE test proposed in MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting by Biggs, Schrab, and Gretton: https://arxiv.org/abs/2306.08777

Enitor provides the MATLAB implementation of several large-scale kernel methods.

Gmmn Pytorch ⭐ 5

Implementation of Generative Moment Matching Networks in pytorch

1-63 of 63 search results

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