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Antoine Siraudin

2 accepted papers

2025

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

ICML 2025poster

While machine learning on graphs has demonstrated promise in drug design and molecular property prediction, significant benchmarking challenges hinder its further progress and relevance. Current benchmarking practices often lack focus on transformative, real-world applications, favoring narrow domai…

Cited by 1SourcePDFScholar
2023

DiGress: Discrete Denoising diffusion for graph generation

ICLR 2023poster

This work introduces DiGress, a discrete denoising diffusion model for generating graphs with categorical node and edge attributes. Our model utilizes a discrete diffusion process that progressively edits graphs with noise, through the process of adding or removing edges and changing the categories.…