Search Results - Autoencoder

Autoencoder in Autoencoder Networks by Zhang, Changqing, Geng, Yu, Han, Zongbo, Liu, Yeqing, Fu, Huazhu, Hu, Qinghua

“… To address this issue, we propose a novel unsupervised multiview representation learning (UMRL) algorithm, termed autoencoder in autoencoder networks…”
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Autoencoder asset pricing models by Gu, Shihao, Kelly, Bryan, Xiu, Dacheng

“… – autoencoder neural networks – to incorporate information from covariates along with returns themselves…”
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AE2-Nets: Autoencoder in Autoencoder Networks by Zhang, Changqing, Liu, Yeqing, Fu, Huazhu

“… Differently, in this paper, we focus on unsupervised representation learning and propose a novel framework termed Autoencoder in Autoencoder Networks (AE^2-Nets…”
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Dirichlet Variational Autoencoder by 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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Blind Denoising Autoencoder by Majumdar, Angshul

“… But there has been no autoencoder-based solution for the said blind denoising approach. So far, autoencoder-based denoising formulations have learned the model on a separate training data and have used the learned model to denoise test samples…”
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Convolutional Autoencoder for Spectral-Spatial Hyperspectral Unmixing by Palsson, Burkni, Ulfarsson, Magnus O., Sveinsson, Johannes R.

“…). In this article, we present a new spectral-spatial linear mixture model and an associated estimation method based on a convolutional neural network autoencoder unmixing (CNNAEU…”
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Autoencoder for words by Liou, Cheng-Yuan, Cheng, Wei-Chen, Liou, Jiun-Wei, Liou, Daw-Ran

“…This paper presents a training method that encodes each word into a different vector in semantic space and its relation to low entropy coding. Elman network is…”
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Context Autoencoder for Self-supervised Representation Learning by Chen, Xiaokang, Ding, Mingyu, Wang, Xiaodi, Xin, Ying, Mo, Shentong, Wang, Yunhao, Han, Shumin, Luo, Ping, Zeng, Gang, Wang, Jingdong

“…We present a novel masked image modeling (MIM) approach, context autoencoder (CAE), for self-supervised representation pretraining…”
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Autoencoders reloaded by Bourlard, Hervé, Kabil, Selen Hande

“…In Bourlard and Kamp (Biol Cybern 59(4):291–294, 1998), it was theoretically proven that autoencoders (AE…”
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DEVDAN: Deep evolving denoising autoencoder by Ashfahani, Andri, Pratama, Mahardhika, Lughofer, Edwin, Ong, Yew-Soon

“…The Denoising Autoencoder (DAE) enhances the flexibility of data stream method in exploiting unlabeled samples…”
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eVAE: Evolutionary Variational Autoencoder by 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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Financial portfolio optimization with online deep reinforcement learning and restricted stacked autoencoder—DeepBreath by Soleymani, Farzan, Paquet, Eric

“…•Extracting high-level features using restricted stacked autoencoder.•A convolutional neural network is employed to enforce the policy…”
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DAEN: Deep Autoencoder Networks for Hyperspectral Unmixing by Su, Yuanchao, Li, Jun, Plaza, Antonio, Marinoni, Andrea, Gamba, Paolo, Chakravortty, Somdatta

“… In this paper, we develop a new technique for unsupervised unmixing which is based on a deep autoencoder network (DAEN…”
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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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Autoencoder-based network anomaly detection by Chen, Zhaomin, Yeo, Chai Kiat, Lee, Bu Sung, Lau, Chiew Tong

“… It is thus a challenging task to determine network anomaly more accurately. In this paper, we propose an Autoencoder-based network anomaly detection method…”
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Heterogeneous Hypergraph Variational Autoencoder for Link Prediction by 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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Autoencoder and Its Various Variants by Zhai, Junhai, Zhang, Sufang, Chen, Junfen, He, Qiang

“…The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning…”
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Hyperspectral Anomaly Detection with Guided Autoencoder by Xiang, Pei, Ali, Shahzad, Jung, Soon Ki, Zhou, Huixin

“…Recently, autoencoder-based hyperspectral anomaly detection methods have demonstrated excellent performance on hyperspectral images (HSIs). The autoencoder (AE…”
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Crash data augmentation using variational autoencoder by 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 by Lim, Kart-Leong, Jiang, Xudong, Yi, Chenyu

“…An autoencoder that learns a latent space in an unsupervised manner has many applications in signal processing…”
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