Keynotes and talks (location: Amphi 4)
9h30 – 10h: Welcome Coffee
10h – 11h: Keynote talk by Florence d’Alché-Buc (Télécom, Institut Polytechnique de Paris), "Supervised Graph Prediction: the key role of loss functions"
11h – 11h20: Josef Hoppe: "Introduction to Abstract Cell Complexes for Network Science and Topological Signal Processing"
11h20 – 11h40: Vincenzo Marco De Luca: "xAI-Drop: Don't use what you cannot explain"
11h40 – 12h: Odilon Duranthon: "Aggregation in GNNs can help: why not going to infinity? an asymptotic analysis"
12h – 13h30: Lunch break
13h30 – 14h30: Keynote talk by Pascal Welke (TU Wien)
"Expressive Graph Embeddings via Homomorphism Counting"
14h30 – 14h50: Shubhanshu Mishra: "Contextual Language Models: Using Spatio-temporal and Social Context via Graphs to improve Language Models" *
14h50 – 15h10: Paul Krzakala: "Any2Graph, a general framework for Supervised Graph Prediction"
15h10 – 15h30: Alexandre Duval: "GNN-driven materials discovery"
* Denotes online talk.
Posters (location: Hall Atrium equipped with 15 panels)
15h30 – 18h: Poster session & Social time
Antonin Joly: "Graph Coarsening with Message-Passing Guarantees"
Josef Hoppe: "Random Abstract Cell Complexes"
George Panagopoulos: "Uplift Modeling Under Limited Supervision"
Maria Jose Guerrero: "Graphical Representation of Landscape Heterogeneity Identification through Unsupervised Acoustic Analysis"
Paul Krzakala: "Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss"
Aref Einizade: "Continuous Product Graph Neural Networks"
Martin Gjorgjevski: "Node Regression on Latent Position Random Graphs via Local Averaging"
Daniele Malitesta: "Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?"
Christos Xypolopoulos: "Graph Linearization Methods for Reasoning on Graphs with Large Language Models"
Francesco Ferrini: "A Self-explainable Heterogeneous GNN for Relational Deep Learning"
Vincenzo Marco De Luca: "xAI-Drop: Don't use what you cannot explain"
Minho Lee: "Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks"
Ali Ramlaoui: "Improving Molecular Modeling with Geometric GNNs: an Empirical Study"
Odilon Duranthon: "Asymptotic generalization error of a single-layer GCN"
Junjie Yang: "Deep Sketched Output Kernel Regression for Structured Prediction", "Exploiting Edge Features in Graph-based Learning with Fused Network Gromov-Wasserstein Distance"
Gabriele Spadaro: "WiGNet: Windowed Vision Graph Neural Network"