Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "12541"
  #_source: array:26 [
    "id" => "12541"
    "slug" => "parallel-resampling-in-the-particle-filter"
    "yearMonth" => "2016-01"
    "year" => "2016"
    "title" => "Parallel Resampling in the Particle Filter"
    "description" => "MURRAY, L.M., LEE, A. et JACOB, P. (2016). Parallel Resampling in the Particle Filter. <i>Journal of Computational and Graphical Statistics</i>, 25(3), pp. 789-805."
    "authors" => array:3 [
      0 => array:3 [
        "name" => "JACOB Pierre"
        "bid" => "B00795650"
        "slug" => "jacob-pierre"
      ]
      1 => array:1 [
        "name" => "MURRAY Lawrence M."
      ]
      2 => array:1 [
        "name" => "LEE Anthony"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:4 [
      0 => "Graphics processing unit"
      1 => "parallel computing"
      2 => "particle methods"
      3 => "Sequential Monte Carlo"
    ]
    "updatedAt" => "2023-01-27 01:00:40"
    "publicationUrl" => "https://doi.org/10.1080/10618600.2015.1062015"
    "publicationInfo" => array:3 [
      "pages" => "789-805"
      "volume" => "25"
      "number" => "3"
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted particles through repeated propagation, weighting, and resampling steps."
      "en" => "Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted particles through repeated propagation, weighting, and resampling steps."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2024-04-19T19:22:02.000Z"
    "docTitle" => "Parallel Resampling in the Particle Filter"
    "docSurtitle" => "Articles"
    "authorNames" => "<a href="/cv/jacob-pierre">JACOB Pierre</a>, MURRAY Lawrence M., LEE Anthony"
    "docDescription" => "<span class="document-property-authors">JACOB Pierre, MURRAY Lawrence M., LEE Anthony</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2016</span>"
    "keywordList" => "<a href="#">Graphics processing unit</a>, <a href="#">parallel computing</a>, <a href="#">particle methods</a>, <a href="#">Sequential Monte Carlo</a>"
    "docPreview" => "<b>Parallel Resampling in the Particle Filter</b><br><span>2016-01 | Articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1080/10618600.2015.1062015" target="_blank">Parallel Resampling in the Particle Filter</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 8.76524
  +"parent": null
}