Graph Neural Network Algorithms and Applications
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Combinatorial Optimization, Graph, and Network Algorithms".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1565
Special Issue Editor
Interests: graph neural networks; knowledge graphs; network anomaly detection; recommender systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Graph neural networks (GNNs) have firmly established themselves as foundational tools in networked data analysis. Their adaptability has led to a myriad of variations tailored for diverse real-world tasks, from social network analysis to traffic forecasting. If your expertise lies in network learning, we urge you to share your groundbreaking research with us. We are particularly interested in innovative GNN algorithms, in-depth theoretical explorations of GNNs, and real-world applications harnessing the power of GNNs. Topics of interest encompass, but are not restricted to: efficient techniques for enhancing encoding and training in GNNs, deeper insights into the mechanics and implications of GNN models and applications, and GNN solutions specifically designed for sectors like healthcare, commerce, biochemistry, and transportation. We hope you will consider contributing to this burgeoning field and being a part of our Special Issue. We look forward to your submissions.
Dr. Xiao Huang
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- graph neural networks
- network embedding
- node classification
- node representation learning
- contrastive learning
- graph embedding
- graph convolutional networks
- social network analysis
- network anomaly detection
