ssvae:半监督文本分类的变体自动编码器的代码
半监督文本分类的变体自动编码器
所有这些存储库都在标题为“用于半监督文本分类的可变自动编码器”的论文中使用。
列表：
data：所有数据文件都保存在此目录中，包括数据，单词嵌入，pretrained_weights。
结果：保存结果模型的目录。
assistant_vae和avae_fixed：在VAE中使用辅助变量的模型，可以产生良好的结果。 它们的不同之处在于是否在生成中固定潜在变量。
SemiSample-S1是带有基于EMA基准的基于采样的优化器的模型
SemiSample-S2是带有VIMCO基线的基于采样的优化器的模型
笔记
该代码有点多余，因为最初的模型是使用辅助变量提出的，但是事实证明，如果没有辅助变量，它也可以很好地工作。 要运行此代码，您可能需要预处理的数据，可以通过给我发送电子邮件（pku.edu.cn上的wead_hsu）获得这些数据。 或者，您也可以使用
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资源详情
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