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.
Submission is restricted to registered participants: submissions will not be considered if the respective author is not registered for the event.
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 !