Lu H, Liu S, Wei H, et al. Deep multi-kernel auto-encoder network for clustering brain functional connectivity data[J]. Neural Networks, 2021, 135: 148-157. 摘要 本研究提出了一种深度学习网络模型,称为深度多核自动编码器聚类网络(DMACN),用于脑疾病的functional connectivity data的聚类。该模型是...
Wu C, Khan Z, Ioannidis S, et al. Deep Kernel Learning for Clustering[C]//Proceedings of the 2020 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2020: 640-648. 摘要翻译 论文提出了一种深度学习方法来发现核(kernels),用于识别样本数据上的类簇。 所...
[16] systematically explored deep clustering from a network structure perspective but did not delve into clustering algorithms involving graph neural networks. Ren et al. [17] examined deep clustering from the perspective of data sources, categorizing it into single-view, semi-supervised, multi-view...
Here, we develop a novel multimodal deep learning method, scMDC, for single-cell multi-omics data clustering analysis. scMDC is an end-to-end deep model that explicitly characterizes different data sources and jointly learns latent features of deep embedding for clustering analysis. Extensive ...
译自:http://sebastianruder.com/multi-task/ 1. 前言 在机器学习中,我们通常关心优化某一特定指标,不管这个指标是一个标准值,还是企业KPI。为了达到这个目标,我们训练单一模型或多个模型集合来完成指定得任务。然后,我们通过精细调参,来改进模型直至性能不再提升。尽管这样做可以针对一个任务得到一个可接受得性能,...
githubcrj / AlphaTree-graphic-deep-neural-network Public forked from weslynn/AlphaTree-graphic-deep-neural-network Notifications You must be signed in to change notification settings Fork 0 Star 0 深度神经网络(DNN)与对抗神经网络(GAN)模型总览图示,建立模型发展路书(roadmap),方便大家的理解与...
Figure 1. Flowchart of proposed schema based on multi-visual collaborative deep network (MV-CDN), which consist of three collaborative network members: fully connected network (FCNet), unchanged sensitivity network (USNet), and changed sensitivity network (CSNet). 3.1. Architecture and Training Proce...
Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network. Biomed. Signal Process. Control 2020, 61, 102027. [Google Scholar] [CrossRef] [PubMed] Naeem, U.; Ali Khan, J.; Alharbi, L.A.; Raza, A.; Khan, W.; Ahmad, I. An Efficient Approach ...
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture,Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoğlu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu Graph Attention Multi-Layer Perception,Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiao...
Clustering is a class of unsupervised learning methods that has been extensively applied and studied in computer vision. Little work has been done to adapt it to the end-to-end training of visual features on large-scale datasets. In this work, we present