Disentangled_Variational_Autoencoder:VAE 和 beta-VAE 的 PyTorch 实现

上传者: 42138716 | 上传时间: 2023-04-17 15:19:38 | 文件大小: 5.04MB | 文件类型: ZIP
解开变分自编码器 PyTorch 实现的论文 团队成员: 安德烈亚斯·斯帕诺普洛斯 ( ) Demetrios Konstantinidis ( ) 存储库结构 目录包含我们迄今为止创建的模型。 一路上还会有更多。 python脚本是主要的可执行文件。 目录包含可用于训练和测试的 colab notebook。 在目录中有一个 ,其中详细解释了变分自动编码器的基本数学概念。 在目录中有一些配置文件可用于创建模型。 在目录中有我们通过使用各种配置运行模型得到的结果。 楷模 目前支持两种模型,一个简单的变分自动编码器和一个解开版本 (beta-VAE)。 模型实现可以在目录中找到。 这些模型是使用PyTorch Lightning开发的。 变分自编码器 变分自编码器是一个生成模型。 它的目标是学习数据集的分布,然后从相同的分布中生成新的(看不见的)数据点。 在下图中,我们可

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