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      "extra_author": "Yihui Ren",
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      "extra_author": "Shinjae Yoo",
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      "extra_author": "Jin Huang",
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  "name": 
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pression-for-3d-sparse-tpc-via-bicephalous-convolutional-autoencoder",
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pression-for-3d-sparse-tpc-via-bicephalous-convolutional-autoencoder",
            
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  "notes": "Real-time data collection and analysis in large 
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  "notes": "Real-time data collection and analysis in large 
            
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experimental facilities present a great challenge across multiple 
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experimental facilities present a great challenge across multiple 
            
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domains, including high energy physics, nuclear physics, and 
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domains, including high energy physics, nuclear physics, and 
            
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cosmology. To address this, machine learning (ML)-based methods for 
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cosmology. To address this, machine learning (ML)-based methods for 
            
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real-time data compression have drawn significant attention. However, 
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real-time data compression have drawn significant attention. However, 
            
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unlike natural image data, such as CIFAR and ImageNet that are 
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unlike natural image data, such as CIFAR and ImageNet that are 
            
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relatively small-sized and continuous, scientific data often come in 
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relatively small-sized and continuous, scientific data often come in 
            
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as three-dimensional (3D) data volumes at high rates with high 
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as three-dimensional (3D) data volumes at high rates with high 
            
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sparsity (many zeros) and non-Gaussian value distribution.",
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sparsity (many zeros) and non-Gaussian value distribution.",
            
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      "display_name": "Real-time data compression",
            
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      "id": "4815ae95-580f-4592-954c-7bd41bf54246",
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      "id": "4815ae95-580f-4592-954c-7bd41bf54246",
            
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      "name": "Real-time data compression",
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      "name": "Real-time data compression",
            
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      "state": "active",
            
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      "display_name": "Sparse data",
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      "display_name": "Sparse data",
            
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      "name": "Sparse data",
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    }
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  ],
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  ],
            
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  "title": "Ef\ufb01cient Data Compression for 3D Sparse TPC via 
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  "title": "Ef\ufb01cient Data Compression for 3D Sparse TPC via 
            
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Bicephalous Convolutional Autoencoder",
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Bicephalous Convolutional Autoencoder",
            
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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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}