Abstract: Contrastive learning has emerged as a prominent approach in Heterogeneous Graph Neural Network (HGNN)-based recommender systems, exhibiting particular efficacy in addressing the sparsity ...

This study proposes a potentially useful improvement on a popular fMRI method for quantifying representational similarity in brain measurements by focusing on representational strength at the single ...

To address this issue, this paper introduces a plug-in-play affinity similarity module (ASM) used in any contrastive learning framework for unsupervised visual representation learning. In this ...

The left panel depicts the Audio-Visual Feature Representation framework and the Contrastive-Generative Synchronization Training methodology. For generative synchronization, we design a Feature ...

Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States ...

Incomplete multi-view clustering with cosine similarity 2022 Pattern Recognition Graph IMC Paper Abbreviation Year ... Structured anchor-inferred graph learning for universal incomplete multi-view ...