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GMLR 2023: Graph Models for Learning and Recognition

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GMLR
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截稿日期:
2022-10-31 Extended
通知日期:
2022-12-05
会议日期:
2023-03-27
会议地点:
Tallinn, Estonia
届数:
2
浏览: 10405   关注: 0   参加: 0

会伴指数 (CP-I)

38.0 / 100
全站第 5,413 名 / 共 5,693 个会议 · 前 96%
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
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会议传承 (20%)
30
社区关注 (10%)
8
资料公开度 (15%)
25

用到的输入: 有据可查的届次：2 · 过去 24 个月打开过本页的研究者：2 人

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置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-04

征稿

GMLR 2023 (Graph Models for Learning and Recognition) is an academic conference held in Tallinn, Estonia on 2023-03-27. The paper submission deadline is 2022-10-31 (extended). Acceptance notifications are sent on 2022-12-05.

Submission deadline EXTENDED to: October 31, 2022 Call for Papers Graph Models for Learning and Recognition (GMLR) Track The 38th ACM Symposium on Applied Computing (SAC 2023) March 27 - April 2, 2023, Tallinn, Estonia http://phuselab.di.unimi.it/GMLR2023 Track Chairs ============ Donatello Conte (University of Tours) Alessandro D'Amelio (University of Milan) Giuliano Grossi (University of Milan) Raffaella Lanzarotti (University of Milan) Jianyi Lin (Università Cattolica del Sacro Cuore) Scientific Program Committee ============================ Annalisa Barla (University of Genoa) Davide Boscaini (Bruno Kessler Foundation) Antonella Carbonaro (University of Bologna) Vittorio Cuculo (University of Milan) Samuel Feng (Sorbonne University Abu Dhabi) Gabriele Gianini (University of Milan) Andreas Henschel (Khalifa University) Francesco Isgrò (University of Naples) Giosuè Lo Bosco (University of Palermo) Alessio Micheli (University of Pisa) Carlos Oliver (ETH Zürich) Maurice Pagnucco (University of New South Wales) Jean-Yves Ramel (University of Tours) Ryan A. Rossi (Adobe Research) (others to be confirmed) Important Dates =============== Submission of regular papers: extended to October 31, 2022 Notification of acceptance/rejection: December 5, 2022 Camera-ready copies of accepted papers: December 13, 2022 SAC Conference: March 27 - April 2, 2023 Motivations and topics ====================== The ACM Symposium on Applied Computing (SAC 2023) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2023 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and will be held in Tallinn, Estonia. The technical track on Graph Models for Learning and Recognition (GMLR) is the second edition and is organized within SAC 2023. This track intends to focus on all aspects of graph-based representations and models for learning and recognition tasks. GMLR spans, but is not limited to, the following topics: ● Graph Neural Networks: theory and applications ● Deep learning on graphs ● Graph or knowledge representational learning ● Graphs in pattern recognition ● Graph databases and linked data in AI ● Benchmarks for GNN ● Dynamic, spatial and temporal graphs ● Graph methods in computer vision ● Human behavior and scene understanding ● Social networks analysis ● Data fusion methods in GNN ● Efficient and parallel computation for graph learning algorithms ● Reasoning over knowledge-graphs ● Interactivity, explainability and trust in graph-based learning ● Probabilistic graphical models ● Biomedical data analytics on graphs Submission Guidelines ===================== Authors are invited to submit original and unpublished papers of research and applications for this track. The author(s) name(s) and address(es) must not appear in the body of the paper, and self-reference should be in the third person. This is to facilitate double-blind review. Please, visit the website for more information about submission. Journal Special Issue ===================== The track committee is working to organize a journal Special Issue, to which the authors of selected top papers of this track will be invited for an extended version. SAC No-Show Policy ================== Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library.
由 Jianyi Lin 最后更新于

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