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20192026
most citedAdversarial Regression. Generative Adversarial Networks for Non-Linear Regression: Theory and Assessment

4 citations · 5 across the 8 of their papers we have counts for

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cs.LG2026

Hierarchical Discrete Flow Matching for Graph Generation

Yoann Boget, Pablo Strasser, Alexandros Kalousis

Denoising-based models, including diffusion and flow matching, have led to substantial advances in graph generation. Despite this progress, such models remain constrained by two fu…

cs.LG2026

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

Yoann Boget, Alexandros Kalousis

Denoising models such as Diffusion or Flow Matching have recently advanced generative modeling for discrete structures, yet most approaches operate directly in the discrete state s…