Topic: kernel-methods Goto Github
Some thing interesting about kernel-methods
Some thing interesting about kernel-methods
kernel-methods,Neural Tangent Kernel (NTK) module for the scikit-learn library
User: 392781
Home Page: https://pypi.org/project/scikit-ntk/
kernel-methods,Implementations of gradKCCA
Organization: aalto-ics-kepaco
kernel-methods,Implementation of Generative Moment Matching Networks in pytorch
User: abhipanda4
Home Page: https://abhipanda4.github.io/gmmn.html
kernel-methods,PyTorch implementation of Stein Variational Gradient Descent
User: activatedgeek
Home Page: https://sanyamkapoor.com/kb/the-stein-gradient
kernel-methods,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"
User: annamalai-nr
kernel-methods,This repository contains the TensorFlow implemtation of subgraph2vec (KDD MLG 2016) paper
User: annamalai-nr
Home Page: https://sites.google.com/site/subgraph2vec/
kernel-methods,Labs and homeworks done during the Master Mathematics, Vision, Learning (MVA) at ENS Paris-Saclay.
User: antoine-moulin
kernel-methods,Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.15073
User: antoninschrab
kernel-methods,Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
Organization: bayeswatch
Home Page: https://arxiv.org/abs/1910.05199
kernel-methods,A collection of important graph embedding, classification and representation learning papers with implementations.
User: benedekrozemberczki
kernel-methods,The code for Principal Component Analysis (PCA), dual PCA, Kernel PCA, Supervised PCA (SPCA), dual SPCA, and Kernel SPCA
User: bghojogh
Home Page: https://arxiv.org/abs/1906.03148
kernel-methods,[IEEE TCYB 2021] Official Python implementation for Unsupervised Change Detection in Multitemporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network
User: chenhongruixuan
kernel-methods,SPLASH is an interactive visualisation and plotting tool using kernel interpolation, mainly used for Smoothed Particle Hydrodynamics simulations
User: danieljprice
Home Page: http://users.monash.edu.au/~dprice/splash
kernel-methods,Implicit generative models and related stuff based on the MMD, in PyTorch
User: djsutherland
kernel-methods,Learning kernels to maximize the power of MMD tests
User: djsutherland
Home Page: https://arxiv.org/abs/1611.04488
kernel-methods,FRP: Fast Random Projections
User: dnbaker
kernel-methods,This is the page for the book Digital Signal Processing with Kernel Methods.
Organization: dspkm
kernel-methods,ManifoldEM Python suite
User: evanseitz
kernel-methods,Large-scale, multi-GPU capable, kernel solver
Organization: falkonml
Home Page: https://falkonml.github.io/falkon/
kernel-methods,Undetected Call of duty: MW, Warzone kernel injector.
User: glitteru
kernel-methods,A package for Multiple Kernel Learning in Python
User: ivanolauriola
kernel-methods,A python package for graph kernels, graph edit distances, and graph pre-image problem.
User: jajupmochi
Home Page: https://graphkit-learn.readthedocs.io
kernel-methods,Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
User: jbramburger
kernel-methods,This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
User: jkfitzsimons
kernel-methods,Python implementation of supervised PCA, supervised random projections, and their kernel counterparts.
Organization: lightonai
Home Page: https://medium.com/@LightOnIO/how-to-perform-supervised-random-projections-with-light-dba9fd20c386
kernel-methods,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
User: lucasrodes
kernel-methods,Quadrature-based features for kernel approximation
User: maremun
kernel-methods,Kernel k Nearest Neighbors in R
User: mlampros
Home Page: https://mlampros.github.io/KernelKnn/
kernel-methods,ML4Chem: Machine Learning for Chemistry and Materials
User: muammar
Home Page: https://ml4chem.dev
kernel-methods,Implementation of LMS, RLS, KLMS and KRLS filters in Python
User: ninja3697
kernel-methods,Learning with operator-valued kernels
Organization: operalib
kernel-methods,A collection of awesome software, libraries, learning tutorials, documents and books, awesome resources and cool stuff about ARM and Windows Exploitation.
User: paulveillard
kernel-methods,Fast radial basis function interpolation for large scale data
Organization: polatory
kernel-methods,Toolkit for training quantum kernels in machine learning applications
Organization: qiskit-community
Home Page: https://arxiv.org/abs/2105.03406
kernel-methods,Foundational library for Kernel methods in pattern analysis and machine learning
User: raamana
Home Page: https://raamana.github.io/kernelmethods/
kernel-methods,
Organization: sag-kelp
Home Page: http://www.kelp-ml.org
kernel-methods,Lazy, structured, and efficient operations with kernel matrices.
User: sebastianament
kernel-methods,Multivariate Local Polynomial Regression and Radial Basis Function Regression
User: sigvaldm
kernel-methods,Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
User: ssydasheng
kernel-methods,A Matlab benchmarking toolbox for kernel adaptive filtering
User: steven2358
kernel-methods,Kernel Methods Toolbox for Matlab/Octave
User: steven2358
kernel-methods,Scala Library/REPL for Machine Learning Research
Organization: tailhq
Home Page: http://tailhq.github.io/DynaML/
kernel-methods,"GRAIL: Efficient Time-Series Representation Learning"
Organization: thedatumorg
kernel-methods,ICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
User: wittawatj
kernel-methods,ICML 2017. Kernel-based adaptive linear-time independence test.
User: wittawatj
kernel-methods,NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
User: wittawatj
kernel-methods,UAI 2015. Kernel-based just-in-time learning for expectation propagation
User: wittawatj
kernel-methods,NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
User: wittawatj
kernel-methods,NeurIPS 2018. Linear-time model comparison tests.
User: wittawatj
kernel-methods,Curated materials for different machine learning related summer schools
User: xuedong
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