Adversarial Regression. Generative Adversarial Networks for Non-Linear Regression: Theory and Assessment. - Yoann Boget (CoRR, 2019)

Permutation Equivariant Generative Adversarial Networks for Graphs. - Yoann Boget; Magda Gregorova; Alexandros Kalousis (CoRR, 2021)

Graph annotation generative adversarial networks. - Yoann Boget; Magda Gregorova; Alexandros Kalousis (ACML, 2022)

GrannGAN: Graph annotation generative adversarial networks. - Yoann Boget; Magda Gregorova; Alexandros Kalousis (CoRR, 2022)

Vector-Quantized Graph Auto-Encoder. - Yoann Boget; Magda Gregorova; Alexandros Kalousis (CoRR, 2023)

Discrete Latent Graph Generative Modeling with Diffusion Bridges. - Van Khoa Nguyen; Yoann Boget; Frantzeska Lavda; Alexandros Kalousis (CoRR, 2024)

Discrete Graph Auto-Encoder. - Yoann Boget; Magda Gregorova; Alexandros Kalousis (Trans. Mach. Learn. Res., 2024)

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization. - Van Khoa Nguyen; Yoann Boget; Frantzeska Lavda; Alexandros Kalousis (AAAI, 2025)

Critical Iterative Denoising: A Discrete Generative Model Applied to Graphs. - Yoann Boget; Alexandros Kalousis (CoRR, 2025)