all AI news
Graph Unitary Message Passing
March 19, 2024, 4:41 a.m. | Haiquan Qiu, Yatao Bian, Quanming Yao
cs.LG updates on arXiv.org arxiv.org
Abstract: Message passing mechanism contributes to the success of GNNs in various applications, but also brings the oversquashing problem. Recent works combat oversquashing by improving the graph spectrums with rewiring techniques, disrupting the structural bias in graphs, and having limited improvement on oversquashing in terms of oversquashing measure. Motivated by unitary RNN, we propose Graph Unitary Message Passing (GUMP) to alleviate oversquashing in GNNs by applying unitary adjacency matrix for message passing. To design GUMP, a …
abstract applications arxiv bias cs.ai cs.lg gnns graph graphs improvement rnn success terms type
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Software Engineering Manager, Generative AI - Characters
@ Meta | Bellevue, WA | Menlo Park, CA | Seattle, WA | New York City | San Francisco, CA
Senior Operations Research Analyst / Predictive Modeler
@ LinQuest | Colorado Springs, Colorado, United States