deep-learning scrna-seq variational-autoencoder variational-bayes single-cell-genomics single-cell-rna-seq deep-generative-model cite-seq human-cell-atlas scverse Updated May 20, 2025 Python RubensZimbres / R
Vamb is a family of metagenomic binners which feeds kmer composition and abundance into a variational autoencoder and clusters the embedding to form bins. Its binners perform excellently with multiple samples, and pretty good on single-sample data. ...
VAE---变分自编码器 1、AE模型回顾 2、关于分布 3、VAE的思路与实现 4、VAE的原理 5、本质 6、总结 1、AE模型回顾 AE(Auto-Encoder)模型,它的逻辑如下所示: 其中,x是真实数据构成的样本空间里面的一个采样值,z是Encoder编码得到的latent code(隐编码),最后经过Decoder解码出来一个接近x的值。 理论上,x的...
To solve the above two problems, we propose a self-adversarial variational autoencoder (adVAE) with a Gaussian anomaly prior assumption. We assume that both the anomalous and the normal prior distribution are Gaussian and have overlaps in the latent space. Therefore, a Gaussian transformer net T...
https://github.com/vaxin/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/variational_autoencoder.py 里面的每一步,都有配合本文章的对照解释。 5. 延伸思考 之所以关注VAE,是从文献[4]引发的,由于视觉早期的概念形成对于之后的视觉认知起了十分关键的作用,我们有理由相信,在神经网络训练时,利用这种递...
要回答什么是 Variational AutoEncoder ,要先讲什么是 AutoEncoder。 AE 由两部分组成:编码器和解码器。 编码器和解码器可以看成两个 function: 编码器用于将高维输入(例如图片)映射到它的 latent representation (中文应该是潜在表示 ?) 解码器会将潜在向量作为输入来创建高维输出,例如生成的图片。 在深度学习中,...
一个流行的框架便是变分自动编码器(Variational Autoencoder, VAE)。VAEs 需要前提假设,但相较于 VAEs 能够模拟的复杂依赖关系而言这些假设引入的误差可以说微不足道。 1.1 隐含参数模型 如果要自动生成手写数字0-9,那么事先决定要生成什么数字是很有必要的。这个决定被称作隐含变量(latent variable)。隐含变量通常...
What is a variational autoencoder? To get an understanding of a VAE, we'll first start from a simple network and add parts step by step. An common way of describing a neural network is an approximation of some function we wish to model. However, they can also be thought of as a data...
你可以从这里获得一些这篇博客的代码:https:///kvfrans/variational-autoencoder 和一个整理好的版本: https://jmetzen.github.io/2015-11-27/vae.html 黄世宇/Shiyu Huang's Personal Page:https://huangshiyu13.github.io/
random.uniform(**args) # Original implementation: https://github.com/chainer/chainer/tree/master/examples/vae class VAE(chainer.Chain): """Variational AutoEncoder""" def __init__(self, n_in, n_latent, n_h, act_func=F.tanh): super(VAE, self).__init__() self.act_func = act_...