Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

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Deep neural architectures for unsupervised graph representation learning

2021/41/N/ST6/03694

Keywords:

graphs representation learning deep neural networks

Descriptors:

  • ST6_7: Artificial intelligence, intelligent systems, multi-agent systems

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Politechnika Wrocławska

woj.

Other projects carried out by the institution 

Principal investigator (from the host institution):

Piotr Bielak 

Number of co-investigators in the project: 2

Call: PRELUDIUM 20 - announced on 2021-03-15

Amount awarded: 92 110 PLN

Project start date (Y-m-d): 2022-02-02

Project end date (Y-m-d): 2024-02-01

Project duration:: 24 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Information in the final report

  • Publication in academic press/journals (2)
  • Articles in post-conference publications (1)
  1. Graph Barlow Twins: A self-supervised representation learning framework for graphs
    Authors:
    Piotr Bielak, Tomasz Kajdanowicz, Nitesh V. Chawla
    Academic press:
    Knowledge-Based Systems (rok: 2022, tom: 256, strony: 109631), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2022.109631 - link to the publication
  2. Graph Barlow Twins: A self-supervised representation learning framework for graphs
    Authors:
    Piotr Bielak, Tomasz Kajdanowicz, Nitesh V. Chawla
    Academic press:
    Knowledge-Based Systems (rok: 2022, tom: 256, strony: 109631), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2022.109631 - link to the publication
  1. Representation learning in multiplex graphs: Where and how to fuse information?
    Authors:
    Piotr Bielak, Tomasz Kajdanowicz
    Conference:
    Lecture Notes in Computer Science (rok: 2024, tom: International Conference on Computational Science 2024, strony: 3--18), Wydawca: Springer Nature Switzerland
    Data:
    konferencja 02-04.07.2024
    Status:
    Published
    DOI:
    10.1007/978-3-031-63778-0_1 - link to the publication

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