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  "Title": "Clustering and Prediction using Multi-Task Gaussian Processes\nwith Common Mean",
  "Version": "1.2.1",
  "Authors@R": "c(\nperson(\"Arthur\", \"Leroy\", , \"arthur.leroy.pro@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0806-8934\")),\nperson(\"Pierre\", \"Latouche\", , \"pierre.latouche@gmail.com\", role = \"aut\"),\nperson(\"Pierre\", \"Pathé\", , \"pathepierre@gmail.com\", role = \"ctb\"),\nperson(\"Alexia\", \"Grenouillat\", , \"grenouil@insa-toulouse.fr\", role = \"ctb\"),\nperson(\"Hugo\", \"Lelievre\", , \"lelievre@insa-toulouse.fr\", role = \"ctb\")\n)",
  "Description": "An implementation for the multi-task Gaussian processes\nwith common mean framework. Two main algorithms, called 'Magma'\nand 'MagmaClust', are available to perform predictions for\nsupervised learning problems, in particular for time series or\nany functional/continuous data applications. The corresponding\narticles has been respectively proposed by Arthur Leroy, Pierre\nLatouche, Benjamin Guedj and Servane Gey (2022)\n<doi:10.1007/s10994-022-06172-1>, and Arthur Leroy, Pierre\nLatouche, Benjamin Guedj and Servane Gey (2023)\n<https://jmlr.org/papers/v24/20-1321.html>. Theses approaches\nleverage the learning of cluster-specific mean processes, which\nare common across similar tasks, to provide enhanced prediction\nperformances (even far from data) at a linear computational\ncost (in the number of tasks).  'MagmaClust' is a\ngeneralisation of 'Magma' where the tasks are simultaneously\nclustered into groups, each being associated to a specific mean\nprocess.  User-oriented functions in the package are decomposed\ninto training, prediction and plotting functions. Some basic\nfeatures (classic kernels, training, prediction) of standard\nGaussian processes are also implemented.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/ArthurLeroy/MagmaClustR,\nhttps://arthurleroy.github.io/MagmaClustR/",
  "BugReports": "https://github.com/ArthurLeroy/MagmaClustR/issues",
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  "Repository": "https://arthurleroy.r-universe.dev",
  "Date/Publication": "2026-03-20 16:19:57 UTC",
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  "Author": "Arthur Leroy [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0806-8934>),\nPierre Latouche [aut],\nPierre Pathé [ctb],\nAlexia Grenouillat [ctb],\nHugo Lelievre [ctb]",
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      "title": "Allocate training data into the most probable cluster",
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    {
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      "title": "Expand a grid of inputs",
      "topics": [
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    },
    {
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      "title": "Generate random hyper-parameters",
      "topics": [
        "hp"
      ]
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    {
      "page": "hyperposterior",
      "title": "Compute the hyper-posterior distribution in Magma",
      "topics": [
        "hyperposterior"
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    },
    {
      "page": "hyperposterior_clust",
      "title": "Compute the hyper-posterior distribution for each cluster in MagmaClust",
      "topics": [
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    {
      "page": "MagmaClustR",
      "title": "MagmaClustR : Clustering and Prediction using Multi-Task Gaussian Processes",
      "topics": [
        "MagmaClustR-package",
        "MagmaClustR"
      ]
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