A collection of important graph embedding, classification and representation learning papers with implementations.
翻译 - 一系列重要的图形嵌入，分类和表示学习论文以及实现。
#计算机科学#Learning kernels to maximize the power of MMD tests
#计算机科学#Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
#计算机科学#Scala Library/REPL for Machine Learning Research
#计算机科学#Large-scale, multi-GPU capable, kernel solver
Fast radial basis function interpolation and kriging for large scale data
A package for Multiple Kernel Learning in Python
#计算机科学#A python package for graph kernels, graph edit distances, and graph pre-image problem.
#计算机科学#Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
A Matlab benchmarking toolbox for kernel adaptive filtering
#计算机科学#ML4Chem: Machine Learning for Chemistry and Materials
#计算机科学#Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
#计算机科学#NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
#计算机科学#[IEEE TCYB 2021] Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network
#计算机科学#NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
SPLASH is an interactive visualisation and plotting tool using kernel interpolation, mainly used for Smoothed Particle Hydrodynamics simulations
Multivariate Local Polynomial Regression and Radial Basis Function Regression
#计算机科学#Implementation of LMS, RLS, KLMS and KRLS filters in Python