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Welcome to the website for LoGAMS, the Amsterdam meetup for the global LoG Conference. Hosted by Elsevier & Vrije Universiteit Amsterdam on November 26 + 27, 2024.

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About

The LoGAMS conference is a satellite event of the global LoG Conference, featuring talks, posters and networking opportunities, aiming to bring together the local community in graph machine learning and geometry.

⚠️ Updated Schedule

Due to external circumstances the schedule of LoGAMS has shifted from November 25 + 26 -> November 26 + 27.

Details

Agenda

By attending LoGAMS, you will have the opportunity to:

Dates

Schedule

Tuesday November 26

Time Event Details
09:30 - 10:00 Registration, coffee & welcome  
10:00 - 10:30 Invited Talk: Kubilay Atasu Graph Machine Learning for Financial Crime Analysis
10:30 - 11:00 Invited Talk: Ralvi Isufaj Connecting the dots: Practical insights and considerations for building graph based recommender systems at scale
11:00 - 11:20 Break  
11:20 - 11:50 Invited Talk: Deepak Patankar Fraud Networks : Detecting fraudster webs through graphs
11:50 - 12:20 Talk: Tianqi Zhao AGALE: A Graph-Aware Continual Learning Evaluation Framework
12:20 - 13:20 Lunch  
13:20 - 15:00 Poster Session Matching Topological Signals (Maosheng Yang)
Bicycle Travel Time Estimation with Graph Neural Networks (Ting Gao)
DNA: Differentially private Neural Augmentation for contact tracing (Rob Romijnders)
AGALE: A Graph-Aware Continual Learning Evaluation Framework (Tianqi Zhao)
Blind identification of overlapping communities from nodal observations ( Ruben Wijnands)
Dataset condensation with latent quantile matching (Wei Wei)
CYCLE: Cross-Year Contrastive Learning in Entity-Linking (Pengyu Zhang)
Hodge-Aware Matched Subspace Detectors (Chengen Liu)
xAI-Drop: Don’t Use What You Cannot Explain (Vincenzo Marco De Luca)
Inverse Design of Copolymers Including Stoichiometry and Chain Architecture (Gabriel Vogel)
Applications of TopoX to Topological Deep Learning (Martin Carrasco)
Graph Neural Networks for Heart Failure Prediction on an EHR-Based Patient Similarity Graph (Heloisa Oss Boll)
Multi-type entity resolution (Alex Ridden)
Joint Embedding Predictive Architecture for Self-supervised Pretraining on Polymer Molecular Graphs (Francesco Piccoli)
Predicting Protein Dynamics of Cryptochrome using Generative Models (Dionessa Biton)
Understanding Feature/Structure Interplay in Graph Neural Networks (Diana Gomes)
15:00 - 15:30 Talk: Rob Romijnders DNA: Differentially private Neural Augmentation for contact tracing
15:30 - 16:00 Talk: Vincenzo Marco De Luca xAI-Drop: Don’t Use What You Cannot Explain
16:00 - 16:20 Break  
16:20 - 16:50 Talk: Gaurav Rattan Learning on Graphs with Weisfeiler-Leman
16:50 - 17:20 Talk: Ana Victória Ladeira From Mission Description to Knowledge Graph: Applying Transformer-based models to map knowledge from publicly available satellite datasets.
17:20 - ~18:30 Drinks  

Wednesday November 27

Time Event Details
09:30 - 10:00 Registration, coffee & welcome  
10:00 - 10:30 Talk: Hosein Azarbonyad Using Knowledge Graphs for QA Extraction from Scientific Articles
10:30 - 11:00 Talk: Liudmila Prokhorenkova Challenges of Generating Structurally Diverse Graphs
11:00 - 11:20 Break  
11:20 - 11:50 Talk: Klim Zaporojets CYCLE: Cross-Year Contrastive Learning in Entity-Linking
11:50 - 12:20 Talk: Andrea Cavallo Spatiotemporal covariance neural networks
12:20 - 13:20 Lunch  
13:20 - 15:00 Poster Session From MLP to NeoMLP: Leveraging Self-Attention for Neural Fields (Miltos Kofinas)
Relative Representations: Topological and Geometric Perspectives (Alejandro Garcia Castellanos)
IID Relaxation by Logical Expressivity: A Research Agenda for Fitting Logics to Neurosymbolic Requirements (Maarten Stol)
Uncertainty Quantification for GNNs (Charlotte Cambier van Nooten)
Explaining Graph Neural Networks for Node Similarity on Graphs (Daniel Daza)
Learning Graph Neural Networks using Exact Compression (Jeroen Bollen)
Explainable Graph Neural Networks Under Fire (Zhong Li)
Quantum Computing for Power Flow Analysis (Zeynab Kaseb)
Enabling Large-Scale Coordination of Electric Vehicles Using Reinforcement Learning (Stavros Orfanoudakis)
PowerNet: Truncated Matrix Power Series as Quasi-Equivariant Layers (Alex Gabel)
Towards Generalised Pre-Training of Graph Models (Alex Davis)
15:00 - 15:30 Talk: Maarten Stol IID Relaxation by Logical Expressivity: A Research Agenda for Fitting Logics to Neurosymbolic Requirements
15:30 - 16:00 Talk: Alex Gabel PowerNet: Truncated Matrix Power Series as Quasi-Equivariant Layers
16:00 - 16:20 Break  
16:20 - 16:50 Talk: Maosheng Yang Matching Topological Signals
16:50 - 17:20 Talk: Miltos Kofinas From MLP to NeoMLP: Leveraging Self-Attention for Neural Fields
17:20 - ~18:30 Close & Networking  

Registration

Are you interested in attending LoGAMS? Please register with this form.

Contact

For any inquiries or questions about LoGAMS, please feel free to get in touch with our organising team.

Organisation

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We are part of a global network of local meetups.