Wasserstein Auto-Encoders

WAE: 使用Wasserstein距离的变分自编码器.

Variational methods for Conditional Multimodal Learning: Generating Human Faces from Attributes

CMMA: 条件多模态学习的变分方法.

Learning Structured Output Representation using Deep Conditional Generative Models

CVAE: 使用深度条件生成模型学习结构化输出表示.

变分自编码器(Variational Autoencoder)

Variational Autoencoder.本文目录： 变分自编码器之“自编码器”：概率编码器与概率解码器 变分自编码器之“变分”：优化目标与重参数化 变分自编码器的各种变体1. 变分自编码器之“自编码器”：概率编码器与概率解码器变...

Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling

高质量GAN采样的枢纽度先验.

Demystifying MMD GANs

GAN的KID评估指标.