Results 61 to 70 of about 123,539 (262)

CONVERT: Contrastive Graph Clustering with Reliable Augmentation

Proceedings of the 31st ACM International Conference on Multimedia, 2023
Contrastive graph node clustering via learnable data augmentation is a hot research spot in the field of unsupervised graph learning. The existing methods learn the sampling distribution of a pre-defined augmentation to generate data-driven augmentations automatically.
Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu   +9 more
openaire   +2 more sources

A Vascular Microphysiological Model of Lung Fibrosis Reveals That Myofibroblasts and IPF Patient‐Derived Fibroblasts Impair Angiogenesis and Vasculogenesis

Advanced Functional Materials, EarlyView.
A microphysiological lung fibrosis model recapitulates myofibroblast–vascular interactions. Induced myofibroblasts and patient‐derived IPF fibroblasts impair angiogenesis and increase vascular permeability via TGF‐β1–driven signaling. Pharmacological interventions with SB 431542 and VEGF supplementation restore vascular morphology and barrier function.
Elena Cambria, Adriana Blazeski, Eunkyung Clare Ko, Tran Thai, Shania Dantes, David A. Barbie, Sarah E. Shelton, Roger D. Kamm   +7 more
wiley   +1 more source

Graph contrastive learning with node-level accurate difference

Fundamental Research
Graph contrastive learning (GCL) has attracted extensive research interest due to its powerful ability to capture latent structural and semantic information of graphs in a self-supervised manner.
Pengfei Jiao, Kaiyan Yu, Qing Bao, Ying Jiang, Xuan Guo, Zhidong Zhao   +5 more
doaj   +1 more source

Two-way Feature Augmentation Graph Convolution Networks Algorithm [PDF]

Jisuanji kexue
Graph convolutional neural network algorithms play a crucial role in the processing of graph structured data.The mainstream mode of existing graph convolutional networks is based on weighted summation of node features using Laplacian matrices,with a ...
LI Mengxi, GAO Xindan, LI Xue
doaj   +1 more source

Isomorph-free generation of 2-connected graphs with applications [PDF]

, 2011
Many interesting graph families contain only 2-connected graphs, which have ear decompositions. We develop a technique to generate families of unlabeled 2-connected graphs using ear augmentations and apply this technique to two problems.
Stolee, Derrick
core   +6 more sources

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Data Augmentation Techniques for fMRI Data: A Technical Survey

IEEE Access
The application of machine learning to fMRI data classification, prediction, and analysis tasks has experienced rapid growth in recent years. However, its implementation has been limited by the relatively small size of labeled fMRI datasets.
Valentina Sanchez, Cicek Guven, Gonzalo Napoles, Marie Safar Postma   +3 more
doaj   +1 more source

IcaGCN: Model Intents via Coactivated Graph Convolution Network for Recommendation

IEEE Access, 2023
In this era of information overload, to better provide personalized content services to users, recommendation systems have greatly improved the efficiency of information distribution.
Jingxue Zhang, Changchun Yang
doaj   +1 more source

Grad and classes with bounded expansion I. decompositions [PDF]

, 2005
We introduce classes of graphs with bounded expansion as a generalization of both proper minor closed classes and degree bounded classes. Such classes are based on a new invariant, the greatest reduced average density (grad) of G with rank r, grad r(G ...
De Mendez, Patrice Ossona, Nesetril, Jaroslav   +1 more
core  

Cross-Fertilizing Strategies for Better EM Mountain Climbing and DA Field Exploration: A Graphical Guide Book

, 2010
In recent years, a variety of extensions and refinements have been developed for data augmentation based model fitting routines. These developments aim to extend the application, improve the speed and/or simplify the implementation of data augmentation ...
Meng, Xiao-Li, van Dyk, David A.
core   +2 more sources