论文标题
在豆豆重建方面保证VAE
On PAC-Bayesian reconstruction guarantees for VAEs
论文作者
论文摘要
尽管其广泛使用和经验成功，但对变异自动编码器（VAE）的行为和性能的理论理解和研究仅在过去几年中才出现。我们通过分析VAE的重建能力，从而利用Pac-Bayes理论的论点来为这一最近的工作做出了贡献。我们在理论重建误差上提供了概括范围，并就VAE目标的正则效应提供了见解。我们通过对经典基准数据集的支持实验来说明我们的理论结果。
Despite its wide use and empirical successes, the theoretical understanding and study of the behaviour and performance of the variational autoencoder (VAE) have only emerged in the past few years. We contribute to this recent line of work by analysing the VAE's reconstruction ability for unseen test data, leveraging arguments from the PAC-Bayes theory. We provide generalisation bounds on the theoretical reconstruction error, and provide insights on the regularisation effect of VAE objectives. We illustrate our theoretical results with supporting experiments on classical benchmark datasets.
