While it's no replacement for either computer, the new device is a powerful alternative for addressing some very practical ...

A relatively simple experiment involving asking a generative AI to compare two objects of very different sizes allows us to ...

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@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 ...

Introduction: Predicting interactions between microRNAs (miRNAs) and messenger RNAs (mRNAs) is crucial for understanding gene expression regulation mechanisms and their roles in diseases. Existing ...

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, ...

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 ...

The opinion addresses common inquiries about when written fee arrangements are required, what they should include, and best practices for lawyers to follow. It emphasizes the importance of written ...