使用VAE结构. 在 Mnist 数据集,隐变量使用 Gumbel-softmax 进行采样. 损失函数使用 KL 损失 + Sigmoid重建损失.
左侧为原始图像,中间部分为 30*10
的隐变量,右侧为重构结果.
可视化 6000 张图片作为输入的 encoder 输出的编码,用T-SNE降维后的结果。 同一种颜色标志的为同类别的图片. 可以看出,编码的聚簇比较合理。
Tensorflow eager for "categorical variational autoencoder using the Gumbel-Softmax estimator"
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