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20232026
most citedDeFoG: Discrete Flow Matching for Graph Generation

1 citations · 1 across the 6 of their papers we have counts for

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cs.LG2026

On Trajectory-Aware Training for Masked Diffusion Language Models

Manuel Madeira, Amitis Shidani, Alice Bizeul +6

Masked diffusion models (MDMs) generate text by unmasking several tokens per step, but they are trained and sampled under different conditions. The model is trained on randomly mas…

cs.LG2025

Generating Directed Graphs with Dual Attention and Asymmetric Encoding

Alba Carballo-Castro, Manuel Madeira, Yiming Qin +2

Directed graphs naturally model systems with asymmetric, ordered relationships, essential to applications in biology, transportation, social networks, and visual understanding. Gen…

cs.LG2024★ 1 cited

DeFoG: Discrete Flow Matching for Graph Generation

Yiming Qin, Manuel Madeira, Dorina Thanou +1

Graph generative models are essential across diverse scientific domains by capturing complex distributions over relational data. Among them, graph diffusion models achieve superior…

cs.LG2024

Generative Modelling of Structurally Constrained Graphs

Manuel Madeira, Clement Vignac, Dorina Thanou +1

Graph diffusion models have emerged as state-of-the-art techniques in graph generation; yet, integrating domain knowledge into these models remains challenging. Domain knowledge is…

cs.LG2023

Tertiary Lymphoid Structures Generation through Graph-based Diffusion

Manuel Madeira, Dorina Thanou, Pascal Frossard

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data, due to their capability of capturing intricate dependencies between biol…