Search Results - "Wasserstein Autoencoder"

Stacked Wasserstein Autoencoder by Xu, Wenju, Keshmiri, Shawn, Wang, Guanghui

“…•A novel stacked Wasserstein autoencoder (SWAE) is proposed to approximate high-dimensional data distribution…”
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Pixel-wise Wasserstein Autoencoder for Highly Generative Dehazing by Kim, Guisik, Park, Sung Woo, Kwon, Junseok

“…We propose a highly generative dehazing method based on pixel-wise Wasserstein autoencoders…”
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A novel wasserstein autoencoder-enhanced thermo-mechanical coupled reduced-order model for high pressure turbine blades life monitoring by Wang, Rongqiao, Chen, Ruoqi, Zhao, Yan, Shen, Tianbao, Chen, Gaoxiang, Hu, Dianyin, Jiang, Zhimin, Wang, Xuemin

“…) blades, a wasserstein autoencoder (WAE)-enhanced thermodynamically coupled reduced-order model (ROM…”
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Accelerating the discovery of anticancer peptides targeting lung and breast cancers with the Wasserstein autoencoder model and PSO algorithm by Yang, Lijuan, Yang, Guanghui, Bing, Zhitong, Tian, Yuan, Huang, Liang, Niu, Yuzhen, Yang, Lei

“… In this work, we report a framework of ACPs generation, which combines Wasserstein autoencoder (WAE…”
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Graph Wasserstein Autoencoder-Based Asymptotically Optimal Motion Planning With Kinematic Constraints for Robotic Manipulation by Xia, Chongkun, Zhang, Yunzhou, Coleman, Sonya A., Weng, Ching-Yen, Liu, Houde, Liu, Shichang, Chen, I-Ming

“… The core of the proposed method is based on a novel neural network model, i.e., graph wasserstein autoencoder (GraphWAE…”
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Generalized Zero-Shot Learning Using Conditional Wasserstein Autoencoder by Kim, Junhan, Shim, Byonghyo

“… In a nutshell, the proposed model, called conditional Wasserstein autoencoder (CWAE), minimizes the Wasserstein distance between the real and generated image feature distributions using an encoder-decoder architecture…”
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A lightweight propagation path aggregating network with neural topic model for rumor detection by Zhang, Pengfei, Ran, Hongyan, Jia, Caiyan, Li, Xuanya, Han, Xueming

“…The structure information associated with message propagation has been proved to be effective to distinguish false and true rumors. However, existing methods…”
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Deterministic Autoencoder using Wasserstein loss for tabular data generation by Wang, Alex X., Nguyen, Binh P.

“… This characteristic also constrains the exploration of latent space interpolation. To address these challenges, we present the Tabular Wasserstein Autoencoder (TWAE…”
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Cycling topic graph learning for neural topic modeling by Liu, Yanyan, Gong, Zhiguo

“…Topic models aim to discover a set of latent topics in a textual corpus. Graph Neural Networks (GNNs) have been recently utilized in Neural Topic Models (NTMs)…”
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Towards a configurable and non-hierarchical search space for NAS by Perrin, Mathieu, Guicquero, William, Paille, Bruno, Sicard, Gilles

“… This embedding is built upon a Wasserstein Autoencoder, regularized by both a Maximum Mean Discrepancy…”
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Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening by Alaverdyan, Zaruhi, Jung, Julien, Bouet, Romain, Lartizien, Carole

“…•We cast the challenging problem of detecting subtle brain lesions as a per voxel outlier detection problem.•Our brain anomaly detection model is trained on…”
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Information preservation with wasserstein autoencoders: generation consistency and adversarial robustness by Chakrabarty, Anish, Basu, Arkaprabha, Das, Swagatam

“…Amongst the numerous variants Variational Autoencoder (VAE) has inspired, the Wasserstein Autoencoder (WAE…”
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SeGMA: Semi-Supervised Gaussian Mixture Autoencoder by Smieja, Marek, Wolczyk, Maciej, Tabor, Jacek, Geiger, Bernhard C.

“…We propose a semi-supervised generative model, SeGMA, which learns a joint probability distribution of data and their classes and is implemented in a typical Wasserstein autoencoder framework…”
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One-shot style transfer using Wasserstein Autoencoder by Nakada, Hidemoto, Asoh, Hideki

“…We propose an image style transfer method based on disentangled representation obtained with Wasser-stein Autoencoder. Style transfer is an area of image…”
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Correlated Wasserstein Autoencoder for Implicit Data Recommendation by Yao, Linying, Zhong, Jingbin, Zhang, Xiaofeng, Luo, Linhao

“… other. To cope with this issue, this paper proposes the correlated Wasserstein autoencoders (CWAEs) model to capture data correlation to enhance recommendation peformance…”
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Sliced Wasserstein based Canonical Correlation Analysis for Cross-Domain Recommendation by Zhao, Zian, Nie, Jie, Wang, Chenglong, Huang, Lei

“…•A cross-domain recommendation model based on Sliced Wasserstein autoencoder is proposed…”
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Generative Data Augmentation via Wasserstein Autoencoder for Text Classification by Jin, Kyohoon, Lee, Junho, Choi, Juhwan, Jang, Soojin, Kim, Youngbin

“… In this paper, we propose a data augmentation method based on the pre-trained language model (PLM) using the Wasserstein autoencoder…”
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Synthetic Aperture Radar Image Generation With Deep Generative Models by Wang, Ke, Zhang, Gong, Leng, Yang, Leung, Henry

“… To alleviate this problem, a novel deep generative model for SAR image generation is proposed, which is an extension of Wasserstein autoencoder…”
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Topic Embedded Representation Enhanced Variational Wasserstein Autoencoder for Text Modeling by Xiang, Zheng, Liu, Xiaoming, Yang, Guan, Liu, Yang

“… To address the above problems, we introduce a hybrid Wasserstein Autoencoder (WAE) with Topic Embedded Representation (TER) for text modeling…”
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Disentangled Recurrent Wasserstein Autoencoder by Han, Jun, Min, Martin Renqiang, Han, Ligong, Li Erran Li, Zhang, Xuan

“… In this paper, we propose recurrent Wasserstein Autoencoder (R-WAE), a new framework for generative modeling of sequential data…”
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