most citedTowards Efficient Molecular Property Optimization with Graph Energy Based Models

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cs.LG2025

ContinualFlow: Learning and Unlearning with Neural Flow Matching

Lorenzo Simone, Davide Bacciu, Shuangge Ma

We introduce ContinualFlow, a principled framework for targeted unlearning in generative models via Flow Matching. Our method leverages an energy-based reweighting loss to softly s…

cs.LG2025

Graph Diffusion that can Insert and Delete

Matteo Ninniri, Marco Podda, Davide Bacciu

Generative models of graphs based on discrete Denoising Diffusion Probabilistic Models (DDPMs) offer a principled approach to molecular generation by systematically removing struct…