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  "author": "Aymene Mohammed Bouayed",
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  "author": "Aymene Mohammed Bouayed",
            
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  "doi": "10.57702/742i3ss5",
            
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  "extra_authors": [
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    {
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    {
            
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      "extra_author": "David Naccache",
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      "extra_author": "David Naccache",
            
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      "name": "latent-space-sampling",
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      "name": "latent-space-sampling",
            
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      "title": "Latent space sampling"
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      "title": "Latent space sampling"
            
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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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      "name": "synthetic-image-generation",
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      "name": "synthetic-image-generation",
            
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      "title": "Synthetic image generation"
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      "title": "Synthetic image generation"
            
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  "name": "simplex-autoencoders",
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  "name": "simplex-autoencoders",
            
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  "notes": "Synthetic data generation is increasingly important due to 
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  "notes": "Synthetic data generation is increasingly important due to 
            
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privacy concerns. While Autoencoder-based approaches have been widely 
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privacy concerns. While Autoencoder-based approaches have been widely 
            
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used for this purpose, sampling from their latent spaces can be 
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used for this purpose, sampling from their latent spaces can be 
            
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challenging. Mixture models are currently the most ef\ufb01cient way 
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challenging. Mixture models are currently the most ef\ufb01cient way 
            
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to sample from these spaces.",
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to sample from these spaces.",
            
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      "name": "Mixture models",
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      "display_name": "Synthetic image generation",
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      "display_name": "Synthetic image generation",
            
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      "id": "8911e0cd-7d66-4021-b2d2-805f44dc28a5",
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      "id": "8911e0cd-7d66-4021-b2d2-805f44dc28a5",
            
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      "name": "Synthetic image generation",
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      "name": "Synthetic image generation",
            
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  ],
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  "title": "Simplex Autoencoders",
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  "title": "Simplex Autoencoders",
            
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}
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}