Search Results - Generative Autoencoder

A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting by Ma, Long, Huang, Ling, Shi, Huifeng

“…–temporal generative autoencoder (STGAE) model to capture the continuous probability distribution of each wind turbine on an arbitrary graph structure…”
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Dual Contradistinctive Generative Autoencoder by Parmar, Gaurav, Li, Dacheng, Lee, Kwonjoon, Tu, Zhuowen

“…We present a new generative autoencoder model with dual contradistinctive losses to improve generative autoencoder that performs simultaneous inference (reconstruction) and synthesis (sampling…”
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Deep Mixture Generative Autoencoders by Ye, Fei, Bors, Adrian G.

“…Variational autoencoders (VAEs) are one of the most popular unsupervised generative models that rely on learning latent representations of data…”
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Application of Generative Autoencoder in De Novo Molecular Design by Blaschke, Thomas, Olivecrona, Marcus, Engkvist, Ola, Bajorath, Jürgen, Chen, Hongming

“… Various generative autoencoders were used to map molecule structures into a continuous latent space and vice versa and their performance as structure generator was assessed…”
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Real-Time Traffic Speed Estimation With Graph Convolutional Generative Autoencoder by Yu, James Jian Qiao, Gu, Jiatao

“… In this paper, we present a novel deep-learning model called graph convolutional generative autoencoder to fully address the real-time traffic speed estimation problem…”
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Spatio‐Temporal Hourly and Daily Ozone Forecasting in China Using a Hybrid Machine Learning Model: Autoencoder and Generative Adversarial Networks by Cheng, Meiling, Fang, Fangxin, Navon, Ionel M., Zheng, Jie, Tang, Xiao, Zhu, Jiang, Pain, Christopher

“…‐scale numerical simulations. In this work, we introduce a hybrid model (VAE‐GAN) combining a generative adversarial network (GAN…”
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AEGAN: Generating imperceptible face synthesis via autoencoder‐based generative adversarial network by Che, Aolin, Yang, Jing‐Hua, Guo, Cai, Dai, Hong‐Ning, Xie, Haoran, Li, Ping

“… Specifically, we design a generative adversarial network (GAN) framework with an autoencoder (AEGAN…”
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Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders by Knop, Szymon, Spurek, Przemyslaw, Mazur, Marcin, Tabor, Jacek, Podolak, Igor

“…Most autoencoder-based generative machine learning models use a two-factor cost function composed of reconstruction error and prior distribution distance…”
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Lifelong Generative Adversarial Autoencoder by Ye, Fei, Bors, Adrian G.

“… One approach in lifelong learning is the generative replay mechanism (GRM) that trains…”
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AEGANAuth: Autoencoder GAN-Based Continuous Authentication With Conditional Variational Autoencoder Generative Adversarial Network by Li, Yantao, Ouyang, Caike, Huang, Hongyu

“… In this article, we present AEGANAuth, a lightweight and effective autoencoder GAN (AEGAN)-based continuous Authentication system for mobile devices using conditional variational autoencoder generative adversarial network (CVAEGAN…”
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The shape variational autoencoder: A deep generative model of part‐segmented 3D objects by Nash, C., Williams, C. K. I.

“…We introduce a generative model of part‐segmented 3D objects: the shape variational auto‐encoder (ShapeVAE…”
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Generative autoencoder to prevent overregularization of variational autoencoder by Ko, YoungMin, Ko, SunWoo, Kim, YoungSoo

“… it. The variational autoencoder is a generative model that performs variational inference to estimate a low…”
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Semisupervised Generative Autoencoder for Single-Cell Data by Trong, Trung Ngo, Mehtonen, Juha, González, Gerardo, Kramer, Roger, Hautamäki, Ville, Heinäniemi, Merja

“… process, thus forming a SemI-SUpervised generative Autoencoder (SISUA) model. The generative model is based on the deep variational autoencoder (VAE…”
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Evolutionary design of conductive pathways using a generative autoencoder by Ignuta-Ciuncanu, Matei C., Stärk, Hannes, Martinez-Botas, Ricardo F.

“… In contrast, our approach integrates topology optimization, constructal theory, and bio-inspired principles via a generative model that couples a variational autoencoder with evolutionary algorithms…”
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Quantized Generative Autoencoder for Audio Spectrograms by Cebedio, M. Celeste, Rabioglio, Lucas A., Micco, Luciana De

“…This study analyzes techniques for compressing generative autoencoders to enable their deployment on resource-constrained devices, addressing the challenges and optimizations required for such environments…”
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Predicting anatomical variations in radiotherapy with a vector quantized variational autoencoder generative model by Zou, Yue, Li, Zhenhao, Zhang, Menghan, Li, Ziwei, Yin, Xiaojie, Yang, Long, Hu, Weigang, Wang, Jiazhou

“… Predicting these changes may benefit adaptive radiotherapy (ART) in nasopharyngeal cancer. Purpose This study proposes a vector quantized variational autoencoder (VQ‐VAE…”
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Prior Images Guided Generative Autoencoder Model for Dual-Camera Compressive Spectral Imaging by Chen, Yurong, Wang, Yaonan, Zhang, Hui

“…Compressive Spectral Imaging (CSI) techniques have attracted considerable attention among researchers for their ability to simultaneously capture spatial and…”
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Marginal region-integrated regressive conditional variational autoencoder-generative adversarial network: A soft sensing enhancement method by Liu, Guo-yu, Zhu, Qun-Xiong, Luo, Yi, Ke, Wei, He, Yan-Lin, Zhang, Yang, Zhang, Ming-Qing, Xu, Yuan

“…, ultimately affecting the fitting performance of soft sensing models. To address this challenge, we propose a marginal Isolation Mega Trend Diffusion with Regressor Conditional Variational Autoencoder-Generative Adversarial Network (IRCVGAN…”
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Credit Card Fraud Detection Based on Improved Variational Autoencoder Generative Adversarial Network by Ding, Yuanming, Kang, Wei, Feng, Jianxin, Peng, Bo, Yang, Anna

“… However, oversampling still has disadvantages. Hence, we improve the generator part of the Variational Autoencoder Generative Adversarial Network (VAEGAN…”
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Component-aware generative autoencoder for structure hybrid and shape completion by Zhang, Fan, Fu, Qiang, Liu, Yang, Li, Xueming

“… In this paper, we propose a novel generative autoencoder that tackles the component combinations for 3D modeling of man-made objects…”
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