Výsledky vyhledávání - "Variational autoencoder"

Dirichlet Variational Autoencoder Autor Joo, Weonyoung, Lee, Wonsung, Park, Sungrae, Moon, Il-Chul

“…•This paper is a study on Dirichlet prior in variational autoencoder.•Our model outperforms baseline variational autoencoders in the perspective of loglikelihood…”
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eVAE: Evolutionary Variational Autoencoder Autor Wu, Zhangkai, Cao, Longbing, Qi, Lei

“…Variational autoencoders (VAEs) are challenged by the imbalance between representation inference and task fitting caused by surrogate loss…”
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Heterogeneous Hypergraph Variational Autoencoder for Link Prediction Autor Fan, Haoyi, Zhang, Fengbin, Wei, Yuxuan, Li, Zuoyong, Zou, Changqing, Gao, Yue, Dai, Qionghai

“… of nodes, which tends to lead to a sub-optimal embedding result. This paper presents a method named Heterogeneous Hypergraph Variational Autoencoder (HeteHG-VAE…”
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Crash data augmentation using variational autoencoder Autor Islam, Zubayer, Abdel-Aty, Mohamed, Cai, Qing, Yuan, Jinghui

“…•Variational Autoencoder (VAE) was used to generate millions of crash samples from only a limited number of training data…”
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Deep Clustering With Variational Autoencoder Autor Lim, Kart-Leong, Jiang, Xudong, Yi, Chenyu

“…An autoencoder that learns a latent space in an unsupervised manner has many applications in signal processing. However, the latent space of an autoencoder…”
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Joint Coding-Modulation for Digital Semantic Communications via Variational Autoencoder Autor Bo, Yufei, Duan, Yiheng, Shao, Shuo, Tao, Meixia

“… In this work, we propose a joint coding-modulation (JCM) framework for digital semantic communications by using variational autoencoder (VAE…”
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3D‐Var data assimilation using a variational autoencoder Autor Melinc, Boštjan, Zaplotnik, Žiga

“… Here, an alternative neural network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three…”
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Outlier detection variational autoencoder Autor Powers, Henry, Edoh, Kossi

“… The paper presents a new model to address these challenges. The model is a combination of graph neural network layers in a variational autoencoder framework…”
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Cloud-VAE: Variational autoencoder with concepts embedded Autor Liu, Yue, Liu, Zitu, Li, Shuang, Yu, Zhenyao, Guo, Yike, Liu, Qun, Wang, Guoyin

“…•The initial concepts in latent space are described as prior distribution obtained by the proposed cloud model-based clustering algorithm.•Variational lower…”
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TrajVAE: A Variational AutoEncoder model for trajectory generation Autor Chen, Xinyu, Xu, Jiajie, Zhou, Rui, Chen, Wei, Fang, Junhua, Liu, Chengfei

“…) and Variational AutoEncoder (VAE) frameworks respectively to generate trajectories. In order of compare the similarity of existing trajectories in our dataset and the generated trajectories, we utilize multiple trajectory similarity metrics. Through several experiments, we demonstrate that our method is more accurate and stable than the baseline…”
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Quaternion Vector Quantized Variational Autoencoder Autor Luo, Hui, Liu, Xin, Sun, Jian, Zhang, Yang

“…Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in generative tasks…”
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design Autor Mak, Hugo Wai Leung, Han, Runze, Yin, Hoover H. F.

“…In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction…”
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Semisupervised Text Classification by Variational Autoencoder Autor Xu, Weidi, Tan, Ying

“… In this paper, a novel model, the semisupervised sequential variational autoencoder (SSVAE), is proposed to tackle this problem…”
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Recognition of geochemical anomalies using a deep variational autoencoder network Autor Luo, Zijing, Xiong, Yihui, Zuo, Renguang

“… In this study, a deep variational autoencoder (VAE) network was used to extract features related to mineralization…”
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Process monitoring using variational autoencoder for high-dimensional nonlinear processes Autor Lee, Seulki, Kwak, Mingu, Tsui, Kwok-Leung, Kim, Seoung Bum

“… In this study, we propose a variational autoencoder (VAE) as a monitoring method that can address…”
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Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder Autor Li, Chunyan, Yao, Junfeng, Wei, Wei, Niu, Zhangming, Zeng, Xiangxiang, Li, Jin, Wang, Jianmin

“… We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for molecular generation with specific properties, which is protein-context-dependent…”
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A robust variational autoencoder using beta divergence Autor Akrami, Haleh, Joshi, Anand A., Li, Jian, Aydöre, Sergül, Leahy, Richard M.

“…) are not present in the training data. Here we focus on variational autoencoders (VAEs). While the VAE is a popular framework for anomaly detection tasks, we observe…”
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Video anomaly detection and localization via Gaussian Mixture Fully Convolutional Variational Autoencoder Autor Fan, Yaxiang, Wen, Gongjian, Li, Deren, Qiu, Shaohua, Levine, Martin D., Xiao, Fei

“…), while anomalies either do not belong to any Gaussian component. The method is based on Gaussian Mixture Variational Autoencoder, which can learn feature representations of the normal samples as a Gaussian Mixture Model trained using deep learning…”
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Remote sensing image captioning via Variational Autoencoder and Reinforcement Learning Autor Shen, Xiangqing, Liu, Bing, Zhou, Yong, Zhao, Jiaqi, Liu, Mingming

“… To this end, we propose a Variational Autoencoder and Reinforcement Learning based Two-stage Multi-task Learning Model (VRTMM…”
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Bimodal variational autoencoder for audiovisual speech recognition Autor Sayed, Hadeer M., ElDeeb, Hesham E., Taie, Shereen A.

“… This paper proposes a Bimodal Variational Autoencoder (BiVAE) model for audiovisual features fusion…”
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