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  "author": "Ishaan Gulrajani",
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  "author": "Ishaan Gulrajani",
            
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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/10.48550/arXiv.2207.10285"
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    "https://doi.org/10.48550/arXiv.2207.10285"
            
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  "doi_date_published": "2024-12-16",
            
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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": "David Lopez-Paz",
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      "extra_author": "David Lopez-Paz",
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Domain Generalization",
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      "display_name": "Domain Generalization",
            
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      "name": "domain-generalization",
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      "name": "domain-generalization",
            
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      "title": "Domain Generalization"
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      "title": "Domain Generalization"
            
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    }
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  ],
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  "landing_page": "https://github.com/dnap512/SelfReg",
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  "name": "domainbed",
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  "name": "domainbed",
            
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  "notes": "The DomainBed dataset is a benchmark for domain 
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  "notes": "The DomainBed dataset is a benchmark for domain 
            
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generalization, containing five multi-domain datasets (VLCS, PACS, 
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generalization, containing five multi-domain datasets (VLCS, PACS, 
            
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OfficeHome, TerraIncognita, and DomainNet). The dataset is used to 
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OfficeHome, TerraIncognita, and DomainNet). The dataset is used to 
            
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evaluate the performance of domain generalization algorithms.",
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evaluate the performance of domain generalization algorithms.",
            
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