Connectionists: Call for papers: ESANN 2021 Special Session on deep Learning for graphs

[Benjamin Paassen]

[Apologies if you receive multiple copies of this CFP]

Call for papers: special session on "Deep learning for graphs"

European Symposium on Artificial Neural Networks, Computational
Intelligence and Machine Learning (ESANN 2021).
6-8 October 2021, Bruges, Belgium - http://www.esann.org

DESCRIPTION:
Graphs are very flexible data structures that can be used to represent,
at the same time, entities and the relationships among them.Graphs can
describe networks of interacting elements, e.g. in social graphs or
metabolomics, as well as data where topological variations influence the
feature of interest, such as molecular compounds.  Data-driven
processing and adaptive learning on structured data has a long-standing
history but it has recently grown to become one of the most active
research topics in the deep learning field. This special session
solicits contributions on the general topic of deep learning for graphs
including wide themes such as graph representation learning, graph
generation, interpretability of deep graph networks, learning for graphs
as a means to integrate symbolic-subsymbolic information. We welcome
works focusing on methodological advances, theoretical works, and also
impacting applications of deep learning for graphs. Topics that are of
interest to this session include, but are not limited to:

TOPICS OF INTEREST (non-exhaustive):

        Deep learning and representation learning for graphs
        Learning with network data
        Learning with knowledge graphs and symbolic-subsymbolic integration
        Graph generation
        Graph coarsening and pooling
        Deep graph networks and combinatorial algorithms/problems
        Interpretable models for graphs
        Randomized neural networks for relational data
        Relational deep learning
        Applications of learning for graphs: e.g. Natural language
processing, machine vision, materials science, chemoinformatics,
computational biology, social networks, federated learning,
recommendation systems.

SUBMISSION:
Prospective authors must submit their paper through the ESANN portal
following the instructions provided in www.esann.org. Each paper will
undergo a peer reviewing process for its acceptance.

IMPORTANT DATES:
Submission of papers: 10 May 2021
Notification of acceptance: 20 July 2019
ESANN conference: 6-8 April 2019

SPECIAL SESSION ORGANISERS:
Davide Bacciu (Università di Pisa, Italy)
Filippo Maria Bianchi (NORCE - the Norwegian Research Center, Norway)
Benjamin Paassen (Humboldt-University of Berlin, Germany)
Cesare Alippi (Università della Svizzera italiana, Switzerland)