self.iscond=isconddefforward(self, x, cond_vec=None): x=self.encoder_cnn(x) x=self.flatten(x)ifself.iscond: x= self.encoder_lin(torch.cat([x, cond_vec], dim=1))else: x=self.encoder_lin(x)returnx Decoder用转置卷积,如下: classDecoder(nn.Module):def__init__(self, encoded_spac...
VAE —— Variational Auto-encoder数据x符合复杂分布pθ(x)。直接根据x建模pθ(x)比较困难,因此引入一个较为简单的先验分布pθ(z),先从简单分布中采样z,再利用z生成x。 VAE的主要思路 VITS任务中,x就是音频,输入的条件是文本大体结构 我们输入训练数据,然后通过编码器降维从中提取关键信息,再通过解码器将提取...
Conditional Variational Autoencoder(CVAE)1是Variational Autoencoder(VAE)2的扩展,在VAE中没有办法对生成的数据加以限制,所以如果在VAE中想生成特定的数据是办不到的。比如在mnist手写数字中,我们想生成特定的数字2,VAE就无能为力了。 因此,CVAE通过对潜层变量和输入数据施加约束,可以生成在某种约束条件下的数据。
一个VAE(variational autoencoder)是一个产生式模型,意味着我们可以产生看起来像我们的训练数据的 samples。 Conditional Variational Autoencoders --- 条件式变换自编码机 Goal of a Variational Autoencoder: 一个VAE(variational autoencoder)是一个产生式模型,意味着我们可以产生看起来像我们的训练数据的 samples。...
Conditional Variational AutoEncoder (CVAE) Deep learning Generative Adversarial Networks (GAN) Generative models Inverse design Supercritical airfoil 1. Introduction In the field of aerodynamics, the inverse design of airfoils forms a class of efficient and powerful design tools in the aircraft industry1...
RecGen is a conditional variational autoencoder for the generation of tyrosine site-specific recombinases selective for the defined DNA target site. The repository contains the code that was used to train the RecGen models. You can find the publication here and the recombinase sequences here Conte...
One such model class, exploiting deep inference networks, is the variational autoencoder (VAE).32,33Inference networks of VAEs take observed data as the input and return a distribution over the latent state. VAEs are, however, often primarily used as tools for dimensionality reduction, where da...
Huang, Y., Peng, X., Ma, J. & Zhang, M. 3DLinker: an E(3) equivariant variational autoencoder for molecular linker design. InProc. 39th International Conference on Machine Learning(eds Chaudhuri, K. et al.) 9280–9294 (PMLR, 2022). ...
This repository contains source code for paper Transformer-based Conditional Variational Autoencoder for Controllable Story Generation: @article{fang2021transformer, title={Transformer-based Conditional Variational Autoencoder for Controllable Story Generation}, author={Fang, Le and Zeng, Tao and Liu, Chao...
UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders *** Update 2021-01-14*** Add journal submission link: https://arxiv.org/abs/2009.03075 *** Update 2020-09-05*** Add performance of our UC-Net on DUT RGBD saliency testing dataset(https://github...