logAMS
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.
About • Dates • Registration • Contact • Organisation
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.
Details
- Meet-up on November 26 + 27, 2024.
- The event is free ✨ to attend.
- Hosted by Elsevier at Radarweg 29a, 1043 NX Amsterdam.
- Coffee and lunch provided.
Agenda
By attending logAMS, you will have the opportunity to:
- Learn from leading experts in the field through keynote talks and research presentations.
- Network with fellow researchers, professionals, and enthusiasts in the community.
- Share your own research and insights during poster sessions and interactive discussions.
- Stay up-to-date with the latest trends and advancements in machine learning on graphs and geometry.
Dates
- October 22, 2024. Registration opens.
- November 14, 2024. Registration closes. After this date we maintain a wait list and registrations are considered up to capacity.
- November 26 + 27, 2024. Conference.
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 | Topological Schrödinger Bridge Matching (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) |
| 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) Guiding diffusion models for antibody sequence and structure co-design with developability properties (Amelia Villegas-Morcillo) PowerNet: Truncated Matrix Power Series as Quasi-Equivariant Layers (Alex Gabel) Understanding Feature/Structure Interplay in Graph Neural Networks (Diana Gomes) |
| 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 | Topological Schrödinger Bridge Matching |
| 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
- Michael Cochez, Vrije Universiteit Amsterdam
- Thom Pijnenburg, Elsevier
- Taraneh Younesian, Vrije Universiteit Amsterdam
- Romy Vos, Vrije Universiteit Amsterdam
- Elvin Isufi, Delft University of Technology
- Megha Khosla, Delft University of Technology
- Fabian Hoppe, Vrije Universiteit Amsterdam
We are part of a global network of local meetups.