kernel-methods

There are 262 repositories under kernel-methods topic.

  • operalib

    Learning with operator-valued kernels

    Language:Python22

  • supervised-random-projections

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

    Language:Python20

  • CovarianceFunctions.jl

    Lazy, structured, and efficient operations with kernel matrices.

    Language:Julia20

  • machine-learning-summer-schools

    Curated materials for different machine learning related summer schools

    Language:Jupyter Notebook19

  • kernel-mod

    NeurIPS 2018. Linear-time model comparison tests.

    Language:Jupyter Notebook18

  • GMMN-Pytorch

    Implementation of Generative Moment Matching Networks in pytorch

    Language:Python18

  • KernelKnn

    Kernel k Nearest Neighbors in R

    Language:R17

  • kernel-ep

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

    Language:MATLAB17

  • stadion

    Causal Modeling with Stationary Diffusions, AISTATS 2024

    Language:Python16

  • igms

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

    Language:Jupyter Notebook16

  • gradKCCA

    Implementations of gradKCCA

    Language:MATLAB16

  • quffka

    Quadrature-based features for kernel approximation

    Language:Python16

  • fsic-test

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

    Language:Python16

  • mmdagg-paper

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

    Language:Jupyter Notebook15

  • ManifoldEM_Python

    ManifoldEM Python suite

    Language:Python15

  • hotstepper

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

    Language:Python15

  • pyrfm

    A library for random feature maps in Python.

    Language:C15

  • kPCA-denoising-python

    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

    Language:Python15

  • PyRKHSstats

    A Python package implementing a variety of statistical methods that rely on kernels (e.g. HSIC for independence testing).

    Language:Python14

  • chbmit-seizure-prediction

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

    Language:Jupyter Notebook13

  • regimechange

    Non-parametric method for estimating regime change in bivariate time series setting.

    Language:Python13

  • jaxkern

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

    Language:Jupyter Notebook12

  • nystrompca

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

    Language:Jupyter Notebook12

  • kelp-input-generator

    Utility project to generate KeLP compliant representations

    Language:Java12

  • koopmania

    a little library to help me with things involving Koopman operators

    Language:Python11

  • kllr

    Kernel Localized Linear Regression (KLLR)

    Language:Python11

  • KernelInterpolation.jl

    Multivariate (generalized) scattered data interpolation with symmetric (conditionally) positive definite kernel functions in arbitrary dimension

    Language:Julia10

  • DeterministicParticleFlowControl

    Repository for Deterministic Particle Flow Control framework

    Language:Python10

  • kernel-cgof

    UAI 2020. Kernel goodness-of-fit tests for conditional density models.

    Language:Python10

  • mmdfuse

    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

    Language:Python9
  • Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation

    Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation

    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.

    Language:Jupyter Notebook9

  • DRR

    Dimensionality Reduction via Regression using Kernel Ridge Regression in R

    Language:R9

  • MLSA

    Tensorflow 2.0 implementation of the M-LSA method.

    Language:Python8

  • NonlinearComponentAnalysis

    Application of principal component analysis capturing non-linearity in the data using kernel approach

    Language:Jupyter Notebook8

  • MultipleKernel-LeastSquares-SupportVectorMachine

    Multiple Kernel Least Squares Suport Vector Machine provide classification model.

    Language:Python8

  • k2abc

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

    Language:MATLAB8