Search Results - Multi-modal graph autoencoder

ZMGA: A ZINB-based multi-modal graph autoencoder enhancing topological consistency in single-cell clustering by Yao, Jiaxi, Li, Lin, Xu, Tong, Sun, Yang, Jing, Hongwei, Wang, Chengyuan

“… To address these challenges, we introduce a topologically consistent multi-modal graph autoencoder…”
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SDC-GAE: Structural Difference Compensation Graph Autoencoder for Unsupervised Multimodal Change Detection by Han, Te, Tang, Yuqi, Chen, Yuzeng, Yang, Xin, Guo, Yuqiang, Jiang, Shujing

“… SDC-GAE utilizes a graph convolutional network (GCN) to extract deep structural features from multimodal images…”
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Hybrid Graph Convolutional Network With Online Masked Autoencoder for Robust Multimodal Cancer Survival Prediction by Hou, Wentai, Lin, Chengxuan, Yu, Lequan, Qin, Jing, Yu, Rongshan, Wang, Liansheng

“… This manuscript proposes a novel hybrid graph convolutional network, entitled HGCN, which is equipped with an online masked autoencoder paradigm for robust multimodal cancer survival prediction…”
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Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder by Jiang, Junhao, Zuo, Yi, Li, Zhiyuan

“… of trajectory prediction. To address these challenges, we propose a cooperative intention enhance multi-modal graph convolutional network (CIE-MGCN…”
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Graph2MDA: a multi-modal variational graph embedding model for predicting microbe–drug associations by Deng, Lei, Huang, Yibiao, Liu, Xuejun, Liu, Hui

“…–drug associations by using variational graph autoencoder (VGAE). We constructed multi-modal attributed graphs based on multiple features of microbes and drugs, such as molecular…”
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Variational graph autoencoder-driven balancing strategy for multimodal multi-objective optimization by Yang, Lei, Zhang, Erlei, Dang, Qianlong

“… Therefore, this paper proposes a multimodal multi-objective evolutionary algorithm driven by variational graph autoencoder (VGAE…”
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MAVGAE: a multimodal framework for predicting asymmetric drug-drug interactions based on variational graph autoencoder by Deng, Zengqian, Xu, Jie, Feng, Yinfei, Dong, Liangcheng, Zhang, Yuanyuan

“…Drug-drug interactions refer to the phenomena wherein the potency, duration, or effectiveness of one or multiple drugs undergo alterations of varying degrees…”
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Radiation therapy response prediction for head and neck cancer using multimodal imaging and multiview dynamic graph autoencoder feature selection by Moslemi, Amir, Osapoetra, Laurentius Oscar, Safakish, Aryan, Sannachi, Lakshmanan, Alberico, David, Czarnota, Gregory J

“…Background External beam radiation therapy is a common treatment for head and neck (H&N) cancers. Radiomic features derived from biomedical images have shown…”
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SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival by Pan, Liangrui, Peng, Yijun, Li, Yan, Wang, Xiang, Liu, Wenjuan, Xu, Liwen, Liang, Qingchun, Peng, Shaoliang

“… This paper introduces SELECTOR, a heterogeneous graph-aware network based on convolutional mask encoders for robust multimodal prediction of cancer patient survival…”
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Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders by Yang, Carl, Zhang, Jieyu, Wang, Haonan, Li, Sha, Kim, Myungwan, Walker, Matt, Xiao, Yiou, Han, Jiawei

“… However, relations in social networks are often hard to profile, due to noisy multi-modal signals and limited user-generated ground-truth labels…”
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Dual Mutual Information-Driven Multimodal Recommendation with Denoising Graph Autoencoder by Yang, Mengduo, Zhou, Jie, Xi, Meng, Pan, Xiaohua, Li, Ying, Wu, Yangyang, Zhang, Jinshan, Yin, Jianwei

“… Such limitations ultimately harm the recommendation performance. To this end, we propose a Dual Mutual Information-Driven Multimodal Recommendation Model with Denoising Graph Autoencoder (DMIGA…”
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Spatially Aware Domain Adaptation Enables Cell Type Deconvolution from Multi-Modal Spatially Resolved Transcriptomics by Wang, Lequn, Bai, Xiaosheng, Zhang, Chuanchao, Shi, Qianqian, Chen, Luonan

“… SpaDA utilizes a self-expressive variational autoencoder, coupled with deep spatial distribution alignment, to learn and align spatial and graph representations from spatial multi-modal SRT data…”
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Design of an Iterative Method for Enhanced Multimodal Time Series Analysis Using Graph Attention Networks, Variational Graph Autoencoders, and Transfer Learning by Kamble, Vijaya, Bhargava, Sanjay

“…In the ever-evolving landscape of data analysis, the need to efficiently and accurately interpret multimodal time series data has become paramount…”
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Single-cell RNA-seq data analysis using graph autoencoders and graph attention networks by Feng, Xiang, Fang, Fang, Long, Haixia, Zeng, Rao, Yao, Yuhua

“… In this study, we developed scGAEGAT, a multi-modal model with graph autoencoders and graph attention networks for scRNA-seq analysis based on graph neural networks…”
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Fusion Learning of Multimodal Neuroimaging with Weighted Graph AutoEncoder by Shi, Gen, Zhu, Yifan, Zhang, Fuquan, Liu, Wenjin, Yao, Yuxiang, Li, Xuesong

“… Fusion of multimodal neuroimaging data is expected to provide more comprehensive characterization of brain diseases, given that the different modalities contain more complementary information…”
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Deep graph embedding learning based on multi-variational graph autoencoders for POI recommendation by Gong, Weihua, Shen, Genhang, Zhao, Anlun, Yang, Lianghuai, Cheng, Zhen

“… To address this challenge, we propose a new unified heterogeneous graph embedding framework by leveraging multimodal variational graph autoencoders, called MultiVGAE…”
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Multi-view representation model based on graph autoencoder by Li, Jingci, Lu, Guangquan, Wu, Zhengtian, Ling, Fuqing

“… However, most existing graph representation learning ignores data's multi-modal features and takes the node features and graph structure features as one view…”
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A graph-based semi-supervised approach to classification learning in digital geographies by Liu, Pengyuan, De Sabbata, Stefano

“…As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday…”
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Explicit semantic guided bi-incomplete multi-modal hashing with label co-occurrence and label graph constraints by Zhu, Haoran, Lu, Xu, Zhang, Liang, Liu, Li, Zhang, Huaxiang

“…•We propose LaDiff-BIMH, a novel bi-incomplete multi-modal hashing framework that simultaneously handles missing features and labels within a unified architecture…”
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Multi-modal Spatial Clustering for Spatial Transcriptomics Utilizing High-resolution Histology Images by Li, Bingjun, Karami, Mostafa, Junayed, Masum Shah, Nabavi, Sheida

“…Understanding the intricate cellular environment within biological tissues is crucial for uncovering insights into complex biological functions. While…”
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