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@@ -17,6 +17,6 @@ This trained model reproduces the results of the official implementation of [1].
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  | Model | Dataset | Metric | Obtained value | Reference value |
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  |:---:|:---:|:---:|:---:|:---:|
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- | PoincareVAE | MNIST | NLL | 101.97 (0.01) | 101.47 (0.01) |
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  [1] Mathieu, E., Le Lan, C., Maddison, C. J., Tomioka, R., & Teh, Y. W. (2019). Continuous hierarchical representations with poincaré variational auto-encoders. Advances in neural information processing systems, 32.
 
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  | Model | Dataset | Metric | Obtained value | Reference value |
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  |:---:|:---:|:---:|:---:|:---:|
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+ | PoincareVAE | MNIST | NLL | 101.66 (0.00) | 101.47 (0.01) |
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  [1] Mathieu, E., Le Lan, C., Maddison, C. J., Tomioka, R., & Teh, Y. W. (2019). Continuous hierarchical representations with poincaré variational auto-encoders. Advances in neural information processing systems, 32.