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  "author": "Zepu Wang",
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  "author": "Zepu Wang",
            
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  "doi": "10.57702/25ofgng7",
            
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  "doi_date_published": "2024-12-03",
            
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  "extra_authors": [
            
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    {
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      "extra_author": "Dingyi Zhuang",
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      "extra_author": "Dingyi Zhuang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Yankai Li",
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      "extra_author": "Yankai Li",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Jinhua Zhao",
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Peng Sun",
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      "extra_author": "Peng Sun",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Shenhao Wang",
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      "extra_author": "Shenhao Wang",
            
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      "orcid": ""
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      "orcid": ""
            
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    },
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    {
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      "extra_author": "Yulin Hu",
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      "extra_author": "Yulin Hu",
            
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  "notes": "Traffic data serves as a fundamental component in both 
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  "notes": "Traffic data serves as a fundamental component in both 
            
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research and applications within intelligent transportation systems. 
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research and applications within intelligent transportation systems. 
            
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However, real-world transportation data, collected from loop detectors 
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However, real-world transportation data, collected from loop detectors 
            
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or similar sources, often contains missing values (MV), which can 
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or similar sources, often contains missing values (MV), which can 
            
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adversely impact associated applications and research.",
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adversely impact associated applications and research.",
            
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  "title": "ST-GIN: An Uncertainty Quantification Approach in Traffic 
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Data",
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Data",
            
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