Digital marketing agency for medical practices has been named a winner in the Branding + Identity + Logos category of ...
@article{zhang2025disentangled, title={Disentangled contrastive learning for fair graph representations}, author={Zhang, Guixian and Yuan, Guan and Cheng, Debo and Liu, Lin and Li, Jiuyong and Zhang, ...
Is your feature request related to a problem? Please describe. The cluster graphical representations in resources page is currently a modal over the resources pages, w/o direct URL to get this modal ...
Abstract: In the field of graph self-supervised learning (GSSL), graph autoencoders and graph contrastive learning are two mainstream methods. Graph autoencoders aim to learn representations by ...
Abstract: Recently emerged label noise-resistant graph representation learning (LNR-GRL) has received increasing attention, which aims to enhance the generalization of graph neural networks (GNNs) in ...
Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States Amphionic Inc, Ann Arbor, Michigan 48109, United States Department of Chemical Engineering, ...
Data visualization is the graphical representation of information and data via visual elements like charts, graphs, and maps. It allows decision-makers to understand and communicate complex ideas to ...
Electroencephalography (EEG) holds immense potential for decoding complex brain patterns associated with cognitive states and neurological conditions. In this paper, we propose an end-to-end framework ...
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