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authornunzip <np.scarh@gmail.com>2019-03-10 19:51:34 +0000
committernunzip <np.scarh@gmail.com>2019-03-10 19:51:34 +0000
commit3b7847633545673117eff53f66f47db519ad6cf2 (patch)
treed60c8f4489becbe36f068734101a446bbb0e241f
parentd5e414f34e968fe18ff287591b7dbffec910314b (diff)
downloade4-gan-3b7847633545673117eff53f66f47db519ad6cf2.tar.gz
e4-gan-3b7847633545673117eff53f66f47db519ad6cf2.tar.bz2
e4-gan-3b7847633545673117eff53f66f47db519ad6cf2.zip
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@@ -153,26 +153,22 @@ with L2-Net logits.
$$ \textrm{IS}(x) = \exp(\mathbb{E}_x \left( \textrm{KL} ( p(y\mid x) \| p(y) ) \right) ) $$
-```
\begin{table}[]
\begin{tabular}{llll}
-& \begin{tabular}[c]{@{}l@{}}Test \\ Accuracy \\ (L2-Net)\end{tabular} & \begin{tabular}[c]{@{}l@{}}Inception \\ Score \\ (L2-Net)\end{tabular} & \begin{tabular}[c]{@{}l@{}}Execution \\ time\\ (Training \\ GAN)\end{tabular} \\ \hline
- Shallow CGAN & 0.645 & 3.57 & 8:14 \\
- Medium CGAN & 0.715 & 3.79 & 10:23 \\
- Deep CGAN & 0.739 & 3.85 & 16:27 \\
- Convolutional CGAN & 0.737 & 4 & 25:27 \\
-
- \begin{tabular}[c]{@{}l@{}}Medium CGAN\\ One-sided label \\ smoothing\end{tabular} & 0.749 & 3.643 & 10:42 \\
- \begin{tabular}[c]{@{}l@{}}Convolutional CGAN\\ One-sided label \\ smoothing\end{tabular} & 0.601 & 2.494 & 27:36 \\
- \begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Dropout 0.1\end{tabular} & 0.761 & 3.836 & 10:36 \\
- \begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Dropout 0.5\end{tabular} & 0.725 & 3.677 & 10:36 \\
- \begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Virtual Batch \\ Normalization\end{tabular} & ? & ? & ? \\
- \begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Virtual Batch \\ Normalization\\ One-sided label \\ smoothing\end{tabular} & ? & ? & ? \\
- *MNIST original & 0.9846 & 9.685 & N/A
-
+ & \begin{tabular}[c]{@{}l@{}}Test \\ Accuracy \\ (L2-Net)\end{tabular} & \begin{tabular}[c]{@{}l@{}}Inception \\ Score \\ (L2-Net)\end{tabular} & \begin{tabular}[c]{@{}l@{}}Execution \\ time\\ (Training \\ GAN)\end{tabular} \\ \hline
+Shallow CGAN & 0.645 & 3.57 & 8:14 \\
+Medium CGAN & 0.715 & 3.79 & 10:23 \\
+Deep CGAN & 0.739 & 3.85 & 16:27 \\
+Convolutional CGAN & 0.737 & 4 & 25:27 \\
+\begin{tabular}[c]{@{}l@{}}Medium CGAN\\ One-sided label \\ smoothing\end{tabular} & 0.749 & 3.643 & 10:42 \\
+\begin{tabular}[c]{@{}l@{}}Convolutional CGAN\\ One-sided label \\ smoothing\end{tabular} & 0.601 & 2.494 & 27:36 \\
+\begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Dropout 0.1\end{tabular} & 0.761 & 3.836 & 10:36 \\
+\begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Dropout 0.5\end{tabular} & 0.725 & 3.677 & 10:36 \\
+\begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Virtual Batch \\ Normalization\end{tabular} & ? & ? & ? \\
+\begin{tabular}[c]{@{}l@{}}Medium CGAN\\ Virtual Batch \\ Normalization\\ One-sided label \\ smoothing\end{tabular} & ? & ? & ? \\
+*MNIST original & 0.9846 & 9.685 & N/A
\end{tabular}
\end{table}
-```
# Re-training the handwritten digit classifier