作为Comate,由文心一言驱动的智能编程助手,我将为你详细解答关于Vector Quantized Variational Autoencoder(VQ-VAE)的问题。 1. 变分自编码器(Variational Autoencoder, VAE) 变分自编码器是一种生成模型,旨在学习数据的有效表示(编码)和从这些表示中生成新数据(解码)。与传统的自编码器不同,VAE通过引入潜在
Introduced a novel vector quantized variational autoencoder (VQVAE) framework for robust anomaly detection.Utilized pyramid criss-cross attention (PCCA) modules to enhance feature encoding and reconstruction.Effectively presented normal and abnormal features by using orthogonal subspace constraints (OSCs)....
This study introduces FactorVQVAE, the first integration of the Vector Quantized Variational Autoencoder (VQVAE) into factor modeling, providing a novel framework for predicting cross-sectional stock returns and constructing systematic investment portfolios. The model employs a two-stage architecture to ...
#ai创造营# VQ-VAE-2(Vector Quantized Variational Autoencoder 2)是由DeepMind推出的一种自编码器模型,旨在解决生成模型在图像生成、语音生成和其他多模态任务中的问题。作为VQ-VAE的继任者,VQ-VAE-2在基...
This is a PyTorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937). You can find the author'soriginal implementation in Tensorflow herewithan example you can run in a Jupyter notebook. Installing Dependencies ...
VQ-GAN (Vector Quantized GAN) 是于 2020 年提出的生成对抗网络 (Generative Adversarial Network, GAN) 架构,这种模型架构建立在以下基础上:变分自编码器 (Variational Autoencoder, VAE)学习到的表示可以是离散的,而不仅是连续的。这种模型称为Vector Quantized VAE(VQ-VAE),能够用于生成高质量的图像,同时避免了...
This repository contains my PyTorch implementation of the Vector Quantized Variational Auto Encoder as described by van den Oord et al in Neural Discrete Representation Learning applied to images (source of the architecture figure). The implementation was built according to the description in the paper...
SVG- VAE [17] developed an image autoencoder architecture to learn style vectors of fonts, and then used LSTMs [9] fol- lowed by a Mixture Density Network [3] to generate the SVG drawing sequence. DeepSVG [5] adopted a hierarchi- cal generat...
One recent, commonly used model that quantizes images into integer tokens is theVector-quantized Variational AutoEncoder(VQVAE), a CNN-based auto-encoder whose latent space is a matrix of discrete learnable variables, trained end-to-end.VQGANis an improved version of this that introduces anadver...
This paper presents a finite-rate deep-learning (DL)-based channel state information (CSI) feedback method for massive multiple-input multiple-output (MIMO) systems. The presented method provides a finite-bit representation of the latent vector based on a vector-quantized variational autoencoder (...