Connectionists: [CFP] ESANN 2027 Special Session on New Frontiers in Graph Neural Networks

[Riccardo Cappi]

Dear colleagues,

We are organizing a special session at ESANN 2027, the 35th European
Symposium on Artificial Neural Networks, Computational Intelligence and
Machine Learning, and we invite you to submit your original research
findings.

*SPECIAL SESSION*
New Frontiers in Graph Neural Networks: Emerging Architectures and Training
Paradigms <https://www.esann.org/special-sessions#session3>

ESANN 2027 - Bruges (Belgium) and Online
21-23 April 2027
https://www.esann.org

*IMPORTANT DATES*

Paper submission deadline:   18 November 2026 (AoE)
Notification of acceptance:  22 January 2027
Conference:  21-23 April 2027, Bruges (Belgium)

*SESSION DESCRIPTION*
Graph Neural Networks have become a leading framework for learning from
relational and graph-structured data. However, the growing scale and
complexity of real-world graphs are exposing the limitations of
conventional message-passing architectures and standard training methods.
This special session will focus on emerging graph learning models that
exploit topological, geometrical, spectral, physical, and dynamical
principles. It will also cover novel training paradigms aimed at improving
scalability, data efficiency, memory usage, and energy consumption. Topics
include but are not limited to:

  - Graph representation learning
  - Advanced graph neural architectures
  - Backpropagation-free graph learning
  - Graph structure learning and relational inference
  - Theory of graph neural networks (expressive power, learnability,
negative results)
  - Explainability in graph learning
  - Learning on complex graphs (dynamic graphs, heterogeneous graphs)
  - Randomized neural networks for graphs (e.g. reservoir computing)
  - Recurrent, recursive and contextual models
  - Scalability, data efficiency and training techniques of graph neural
networks
  - Architectures for foundation models operating on graphs
  - Graph datasets and benchmarks

The session aims to connect architectural innovation, theoretical
understanding, and resource-efficient learning to identify promising
directions for the next generation of Graph Neural Networks.

*SUBMISSION NOTES*
Papers submitted to a special session follow exactly the same format,
instructions, deadlines and submission procedure as regular submissions,
and are reviewed according to the same rules. Please remember to indicate
our special session on the paper submission form so that your paper is
routed to us. Papers must not exceed 6 pages, including figures and
references, and must be prepared with the official ESANN LaTeX or Word
template, which you can find here: Author Guidelines
<https://www.esann.org/author_guidelines>. The review process is single
blind. Please check the author guidelines page and the submissions
<https://www.esann.org/node/6> page for the full and up-to-date
instructions.

*ORGANIZERS*
- Riccardo Cappi (corresponding organizer), University of Padua, Italy -
riccardo.cappi at phd.unipd.it
- Caterina Graziani, University of Siena, Italy -
caterina.graziani2 at unisi.it
- Luca Pasa, University of Padua, Italy - luca.pasa at unipd.it
- Nicolò Navarin, University of Padua, Italy - nicolo.navarin at unipd.it
- Pascal Welke, Lancaster University Leipzig, Germany -
p.welke at lancaster.ac.uk
- Franco Scarselli, University of Siena, Italy - franco.scarselli at unisi.it
- Alessandro Sperduti, University of Padua, Italy -
alessandro.sperduti at unipd.it

Please don’t hesitate to contact us if you have any questions. We look
forward to receiving your submissions.

The organizers
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