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author | nunzip <np.scarh@gmail.com> | 2019-03-10 20:12:07 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2019-03-10 20:12:07 +0000 |
commit | f0f101256c3c1394dd5b69998a0699cddfc0d9e6 (patch) | |
tree | 544395d00a22bf77fd9b0a8b43123275fd1de544 /report | |
parent | 3b7847633545673117eff53f66f47db519ad6cf2 (diff) | |
download | e4-gan-f0f101256c3c1394dd5b69998a0699cddfc0d9e6.tar.gz e4-gan-f0f101256c3c1394dd5b69998a0699cddfc0d9e6.tar.bz2 e4-gan-f0f101256c3c1394dd5b69998a0699cddfc0d9e6.zip |
Fix table
Diffstat (limited to 'report')
-rw-r--r-- | report/paper.md | 24 |
1 files changed, 12 insertions, 12 deletions
diff --git a/report/paper.md b/report/paper.md index 3853717..cf479bf 100644 --- a/report/paper.md +++ b/report/paper.md @@ -155,18 +155,18 @@ $$ \textrm{IS}(x) = \exp(\mathbb{E}_x \left( \textrm{KL} ( p(y\mid x) \| p(y) ) \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 + & Accuracy & Inception Sc. & GAN Tr. Time \\ \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 \\ +Medium CGAN+LS & 0.749 & 3.643 & 10:42 \\ +Convolutional CGAN+LS & 0.601 & 2.494 & 27:36 \\ +Medium CGAN DO=0.1 & 0.761 & 3.836 & 10:36 \\ +Medium CGAN DO=0.5 & 0.725 & 3.677 & 10:36 \\ +Medium CGAN+VBN & ? & ? & ? \\ +Medium CGAN+VBN+LS & ? & ? & ? \\ +*MNIST original & 0.9846 & 9.685 & N/A \end{tabular} \end{table} |