5 papers
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 -- properly init…
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…
Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief Propagation
Waïss Azizian, Guillaume Baudart, Marc Lelarge
Exact Bayesian inference on state-space models~(SSM) is in general untractable, and unfortunately, basic Sequential Monte Carlo~(SMC) methods do not yield correct approximations fo…