4 papers · 1 filter
Chaining 2-FWL GNNs for Combinatorial Graph Alignment
Marc Lelarge
For the combinatorial graph alignment problem (GAP), finding the node correspondence that maximizes the number of common edges (nce) between two unlabeled graphs, the classical Fra…
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings
Adrien Lagesse, Marc Lelarge
We propose a novel benchmarking methodology for graph neural networks (GNNs) based on the graph alignment problem, a combinatorial optimization task that generalizes graph isomorph…
MiniF2F in Rocq: Automatic Translation Between Proof Assistants -- A Case Study
Jules Viennot, Guillaume Baudart, Emilio Jesùs Gallego Arias +1
In this work, we conduct an experiment using state-of-the-art LLMs to translate MiniF2F into Rocq. The translation task focuses on generating a Rocq theorem based on three sources:…
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
David A. R. Robin, Kevin Scaman, Marc Lelarge
We present a framework to define a large class of neural networks for which, by construction, training by gradient flow provably reaches arbitrarily low loss when the number of par…