Yoann Boget

Pablo Strasser

CoRR, April, 2026

Unrestrained Simplex Denoising for Discrete Data. A Non-Markovian Approach Applied to Graph Generation.

[BibT_eX]

[DOI]

CoRR, March, 2026

2025

Critical Iterative Denoising: A Discrete Generative Model Applied to Graphs.

[BibT_eX]

[DOI]

CoRR, March, 2025

Simple and Critical Iterative Denoising: A Recasting of Discrete Diffusion in Graph Generation.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Discrete Graph Auto-Encoder.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Discrete Latent Graph Generative Modeling with Diffusion Bridges.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Vector-Quantized Graph Auto-Encoder.

[BibT_eX]

[DOI]

CoRR, 2023

2022

GrannGAN: Graph annotation generative adversarial networks.

[BibT_eX]

[DOI]

CoRR, 2022

Graph annotation generative adversarial networks.

[BibT_eX]

[DOI]

Proceedings of the Asian Conference on Machine Learning, 2022

2021

Permutation Equivariant Generative Adversarial Networks for Graphs.

[BibT_eX]

[DOI]

CoRR, 2021

2019

Adversarial Regression. Generative Adversarial Networks for Non-Linear Regression: Theory and Assessment.

[BibT_eX]

[DOI]