Keriven, Nicolas

10 publications

NeurIPS 2025 Taxonomy of Reduction Matrices for Graph Coarsening Antonin Joly, Nicolas Keriven, Aline Roumy

JMLR 2024 Convergence of Message-Passing Graph Neural Networks with Generic Aggregation on Large Random Graphs Matthieu Cordonnier, Nicolas Keriven, Nicolas Tremblay, Samuel Vaiter

TMLR 2024 Gradient Scarcity in Graph Learning with Bilevel Optimization Hashem Ghanem, Samuel Vaiter, Nicolas Keriven

NeurIPS 2024 Graph Coarsening with Message-Passing Guarantees Antonin Joly, Nicolas Keriven

NeurIPS 2023 What Functions Can Graph Neural Networks Compute on Random Graphs? the Role of Positional Encoding Nicolas Keriven, Samuel Vaiter

NeurIPS 2022 Not Too Little, Not Too Much: A Theoretical Analysis of Graph (over)smoothing Nicolas Keriven

NeurIPS 2021 On the Universality of Graph Neural Networks on Large Random Graphs Nicolas Keriven, Alberto Bietti, Samuel Vaiter

NeurIPS 2020 Convergence and Stability of Graph Convolutional Networks on Large Random Graphs Nicolas Keriven, Alberto Bietti, Samuel Vaiter

AISTATS 2019 Support Localization and the Fisher Metric for Off-the-Grid Sparse Regularization Clarice Poon, Nicolas Keriven, Gabriel Peyré

NeurIPS 2019 Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven, Gabriel Peyré