Article Instance

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{
    "pk": 31681,
    "title": "Representation of Temporal Patterns in Recurrent Networks",
    "subtitle": null,
    "abstract": "In order to determine the manner in which\ntemporal patterns are represented in recurrent\nneural networks, networks trained on a vari-\nety of sequence recognition tasks are exam-\nined. Analysis of the state space of unit ac-\ntivations allows a direct view of the means em-\nployed by the network to solve a given prob-\nlem, and yields insight both into the class of\nsolutions these networks cfm produce and h o w\nthese will generalise to sequences outside the\ntraining set. This intuitive approach helps in\nassessing the potential of recurrent networks\nfor a variety of modelling problems.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Submitted Presentations",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/0qr0z21m",
    "frozenauthors": [
        {
            "first_name": "Fred",
            "middle_name": "",
            "last_name": "Cummins",
            "name_suffix": "",
            "institution": "Indiana University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1993-01-01T21:00:00+03:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/31681/galley/22749/download/"
        }
    ]
}