Thursday, March 9, 2023
| Time | Event | (+) |
| 09:45 - 10:00 | Opening remarks - Introduction to the workshop | |
| 10:00 - 11:00 | (Invited talk) The stochastic blockmodel for clustering nodes in graphs and hypergraphs - Catherine Matias (Building A - Plenary Room) - Catherine Matias |
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| 11:00 - 12:00 | Contributed talks (Building A - Plenary Room) | (+) |
| 11:00 - 11:20 | › DIGRAC: Digraph Clustering Based on Flow Imbalance - Yixuan He, University of Oxford | |
| 11:20 - 11:40 | › SSSNET: Semi-Supervised Signed Network Clustering - Yixuan He, University of Oxford | |
| 11:40 - 12:00 | › Machine learning meets false discovery rate: application to graph anomaly detection - Ariane Marandon-Carlhian, Laboratoire de Probabilités, Statistique et Modélisation | |
| 12:00 - 13:30 | Lunch break | |
| 13:30 - 14:30 | (Invited talk) Opportunities and challenges of graph learning in biomedicine - Pietro Lio (Building A - Plenary Room) - Pietro Lio |
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| 14:30 - 15:30 | Contributed talks (Building A - Plenary Room) | (+) |
| 14:30 - 14:50 | › Adding semantic to level-up graph-based Android malware detection - Roxane Cohen, Laboratoire dánalyse et modélisation de systèmes pour láide à la décision, CEntre de REcherches en MAthématiques de la DEcision | |
| 14:50 - 15:10 | › Graph Neural Network go grammatical - Jason Piquenot, Laboratoire dÍnformatique Fondamentale et Appliquée de Tours, Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes | |
| 15:10 - 15:30 | › MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian - Yixuan He, University of Oxford | |
| 15:30 - 16:00 | Coffee break (Building A - Plenary Room) | |
| 16:00 - 17:00 | (Invited talk) Learning distances for attributed graphs with optimal transport- Pierre Borgnat (Building A - Plenary Room) - Pierre Borgnat |
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| 17:00 - 18:00 | Contributed talks (Building A - Plenary Room) | (+) |
| 17:00 - 17:20 | › Transductive Kernels for Gaussian Processes on Graphs - Yin-Cong Zhi, University of Oxford [Oxford] | |
| 17:20 - 17:40 | › Learning Label Initialization for Time-Dependent Harmonic Extension - Amitoz Azad, Université de Caen Normandie | |
| 17:40 - 18:00 | › Dynamic Ranking and Translation Synchronization - Eglantine Karlé, INRIA |
Friday, March 10, 2023
| Time | Event | (+) |
| 09:00 - 10:00 | (Invited talk) Ranking from pairwise comparisons: a near-linear time minimax optimal algorithm for learning BTL weights - Julien Hendrickx (Building A - Plenary Room) - Julien Hendrickx |
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| 10:00 - 10:30 | Coffee break (Building A - Plenary Room) | |
| 10:30 - 11:30 | Contributed talks (Building A - Plenary Room) | (+) |
| 10:30 - 10:50 | › Curvature-GAT : Improve graph attention with local structural information - Stephane Chretien, Université Lyon 2 | |
| 10:50 - 11:10 | › Non Parametric and Semi-Parametric Modeling of a Sequence of Graphs for Testing Abnormality: Application to Cybersecurity - Clarisse Boinay, Inria Lille - Nord Europe | |
| 11:10 - 11:30 | › Trust and scalability through randomized communication graphs - Jan Ramon, INRIA-Lille | |
| 11:30 - 12:30 | (Invited talk) Graph matching: from fundamental limits to algorithms - Marc Lelarge (Building A - Plenary Room) - Marc Lelarge |
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| 12:30 - 14:00 | Lunch break | |
| 14:00 - 15:00 | (Invited talk) Learning in graphs with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature - Stephane Chretien (Building A - Plenary Room) - Stephane Chretien |
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| 15:00 - 16:00 | Contributed talks (Building A - Plenary Room) | (+) |
| 15:00 - 15:20 | › Graph Neural Networks and Optimal Transport for Distance Learning between Graphs - Aldo Moscatelli, Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes | |
| 15:20 - 15:40 | › Large population limits of Markov processes on random networks - Marvin Lücke, Zuse Institute Berlin | |
| 15:40 - 16:00 | › Temporal network compression via network hashing - Rémi Vaudaine, Réseaux dynamiques : approche structurelle et temporelle |
