VDMv-32 trained on ImageNet32

A variational diffusion model (VDM, https://arxiv.org/abs/2107.00630) trained for the article "DiffEnc: Variational Diffusion with a Learned Encoder" (https://arxiv.org/abs/2310.19789).Model uses v-parametrization for the loss. The diffusion model is of size 32. That is, the diffusion model uses 32 "down-blocks" in the U-net. See details in article.Model was trained on ImageNet32 for 1.5 million steps.Random seeds: 1, 2, 13

一种变分扩散模型（VDM，https://arxiv.org/abs/2107.00630）被用于训练文章《DiffEnc：基于学习编码器的变分扩散》（https://arxiv.org/abs/2310.19789）。该模型在损失函数中采用了v参数化方法。扩散模型的大小为32，即该扩散模型在U-net结构中使用了32个“下采样块”。详细信息请参阅相关文章。模型在ImageNet32数据集上进行了1.5百万步的训练。随机种子：1，2，13。