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{
            
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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "Jose Cribeiro-Ramallo",
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  "author": "Jose Cribeiro-Ramallo",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [
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  "citation": [
            
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    "https://doi.org/10.1145/369082",
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    "https://doi.org/10.1145/369082",
            
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    "https://doi.org/10.48550/arXiv.2207.07732",
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    "https://doi.org/10.48550/arXiv.2207.07732",
            
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    "https://doi.org/10.48550/arXiv.2207.07218",
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    "https://doi.org/10.48550/arXiv.2207.07218",
            
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    "https://doi.org/10.48550/arXiv.2105.12271",
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    "https://doi.org/10.48550/arXiv.2105.12271",
            
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    "https://doi.org/10.48550/arXiv.2407.08094",
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    "https://doi.org/10.48550/arXiv.2407.08094",
            
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    "https://doi.org/10.48550/arXiv.2306.10614",
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    "https://doi.org/10.48550/arXiv.2306.10614",
            
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    "https://doi.org/10.48550/arXiv.1803.05814",
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    "https://doi.org/10.48550/arXiv.1803.05814",
            
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    "https://doi.org/10.48550/arXiv.2009.03937"
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    "https://doi.org/10.48550/arXiv.2009.03937"
            
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  ],
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  ],
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2102.00853",
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  "defined_in": "https://doi.org/10.48550/arXiv.2102.00853",
            
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  "doi": "10.57702/8pm531l2",
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  "doi": "10.57702/8pm531l2",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-03",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "domain": "https://service.tib.eu/ldmservice",
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  "domain": "https://service.tib.eu/ldmservice",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Vadim Arzamasov",
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      "extra_author": "Vadim Arzamasov",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    },
            
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    {
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    {
            
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      "extra_author": "Klemens B\u00a8ohm",
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      "extra_author": "Klemens B\u00a8ohm",
            
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      "orcid": ""
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      "orcid": ""
            
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    }
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Density Estimation",
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      "display_name": "Density Estimation",
            
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      "name": "density-estimation",
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      "name": "density-estimation",
            
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      "title": "Density Estimation"
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      "title": "Density Estimation"
            
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      "description": "",
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      "name": "dimensionality-reduction",
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      "name": "dimensionality-reduction",
            
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      "title": "Dimensionality Reduction"
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      "title": "Dimensionality Reduction"
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Multidimensional scaling",
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      "name": "multidimensional-scaling",
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      "name": "multidimensional-scaling",
            
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      "title": "Multidimensional scaling"
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      "title": "Multidimensional scaling"
            
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    },
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    {
            
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      "description": "",
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      "display_name": "Outlier Detection",
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      "image_display_url": "",
            
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      "name": "outlier-detection",
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      "name": "outlier-detection",
            
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      "title": "Outlier Detection"
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      "title": "Outlier Detection"
            
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    },
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Synthetic Datasets",
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      "display_name": "Synthetic Datasets",
            
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      "id": "933e487c-db5a-4a72-ae93-c27cfa3661e8",
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      "id": "933e487c-db5a-4a72-ae93-c27cfa3661e8",
            
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      "image_display_url": "",
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      "image_display_url": "",
            
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      "name": "synthetic-datasets",
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      "name": "synthetic-datasets",
            
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      "title": "Synthetic Datasets"
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      "title": "Synthetic Datasets"
            
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    },
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Time Series Forecasting",
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      "display_name": "Time Series Forecasting",
            
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      "id": "2d0040ff-e50c-4b62-a5dc-c4c0241f05f1",
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      "id": "2d0040ff-e50c-4b62-a5dc-c4c0241f05f1",
            
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      "image_display_url": "",
            
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      "name": "time-series-forecasting",
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      "name": "time-series-forecasting",
            
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      "title": "Time Series Forecasting"
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      "title": "Time Series Forecasting"
            
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    }
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    }
            
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  ],
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  "id": "92ad42a9-5469-4ff9-bd2c-11ed2cb6da34",
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  "isopen": false,
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  "landing_page": "https://example.com/datasets",
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  "license_title": null,
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  "license_title": null,
            
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  "link_orkg": "",
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  "metadata_created": "2024-12-03T10:44:15.564710",
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  "metadata_created": "2024-12-03T10:44:15.564710",
            
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  "metadata_modified": "2024-12-03T10:44:15.564716",
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  "metadata_modified": "2024-12-03T10:44:15.931122",
            
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  "name": "synthetic-datasets",
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  "name": "synthetic-datasets",
            
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  "notes": "The authors used synthetic datasets with temporal 
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  "notes": "The authors used synthetic datasets with temporal 
            
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dependencies and actions. The datasets have 1 million examples, with 
91
dependencies and actions. The datasets have 1 million examples, with 
            
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dimensionality of X t = 20 and ground-truth f is a random neural 
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dimensionality of X t = 20 and ground-truth f is a random neural 
            
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network with three hidden layers of 20 units.",
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network with three hidden layers of 20 units.",
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2024-11-25T12:11:38.292601",
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    "type": "organization"
            
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  "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
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      "created": "2024-12-03T11:31:03",
            
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      "description": "The json representation of the dataset with its 
            
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distributions based on DCAT.",
            
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      "display_name": "multidimensional clustered Gaussian 
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distribution",
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distribution",
            
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      "name": "multidimensional clustered Gaussian distribution",
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      "name": "multidimensional clustered Gaussian distribution",
            
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      "display_name": "multidimensional integration",
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  "title": "Synthetic datasets",
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  "title": "Synthetic datasets",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}