Open Calls

Call for Posters

The meetup will host a local poster session (independent from the main event). We welcome posters from areas broadly related to learning on graphs and geometry. Poster abstracts must be submitted through the submission Google form using LoG LaTeX style files (download or Overleaf Template). 

Submitted posters will be selected by the local organizing team. 

Call for Open Talks

We are planning a session of open talks (a few minutes presentation) on general topics and open problems related to learning on graphs and geometry. Talk abstracts must be submitted through the submission Google form using LoG LaTeX style files (download or Overleaf Template).  If the number of applications exceeds the number of talks that can be included in the session, the organizing committee will reserve the right to select a limited number of talks.

Call for Tutorials - New!

We encourage submitting tutorial proposals on any topic of interest to the LoG audience. A brief description of the tutorial (max 1 page) must be submitted through the submission Google form using LoG LaTeX style files (download or Overleaf Template).  We have a 3-hour slot reserved for tutorials in the schedule, so please include the requested time allocation along with your proposal. 

Registration:

You will be asked to fill out a Google Form and to pay a registration fee of €50 to secure your spot. The fee will cover the cost of the social dinner and coffee breaks.

Submission:

Submit your contribution(s) by following the LoG LaTex file style.

Important dates: 

Registration deadline: November 16, 2024

Submission deadline (both calls): November 16, 2024 

Final decision: November 20, 2024

Registrations and submissions are now closed.

Subject Areas:

Here is a list of LoG’s focus areas, which is not exhaustive. 

• Expressive Graph Neural Networks

• GNN architectures (transformers, new positional encodings, …)

• Equivariant architectures

• Statistical theory on graphs

• Causal inference (structural causal models, …)

• Algorithmic reasoning

• Geometry processing

• Robustness and adversarial attacks on graphs

• Trustworthy graph ML (fairness, privacy, …)

• Combinatorial Optimization and Graph Algorithms

• Geometric and graph generative models (Diffusion, Flow Matching, …)

• Graph Foundation Models

• Graph Kernels

• Graph Signal Processing/Spectral Methods

• Graph Generative Models

• Scalable Graph Learning Models and Methods

• Graphs for Recommender Systems

• Knowledge Graphs

• Graph/Geometric ML for Computer Vision

• Graph ML for Natural Language Processing and LLMs

• Graph/Geometric ML for Molecules (molecules, proteins, drug discovery, …)

• Graph ML for Security

• Graph ML for Health

• Graph/Geometric ML for Physical sciences

• Graph-based approaches in Scientific ML

• Graph ML Platforms and Systems

• Self-supervised learning on graphs

• Graph/Geometric ML Infrastructures (datasets, benchmarks, libraries, …)

• Networks Analysis

• Manifold learning

• Neural manifold

• Geometric optimization

• Structured probabilistic inference

If you doubt that your paper fits the venue, feel free to contact sienalog24@gmail.com !