no code implementations • 28 Dec 2023 • Matteo Ninniri, Marco Podda, Davide Bacciu
This work focuses on the task of property targeting: that is, generating molecules conditioned on target chemical properties to expedite candidate screening for novel drug and materials development.
1 code implementation • 18 Jul 2021 • Marco Podda, Davide Bacciu
Several approaches have been proposed in the literature, most of which require to transform the graphs into sequences that encode their structure and labels and to learn the distribution of such sequences through an auto-regressive generative model.
1 code implementation • 28 Feb 2020 • Marco Podda, Davide Bacciu, Alessio Micheli
Molecule generation is a challenging open problem in cheminformatics.
1 code implementation • 31 Jan 2020 • Davide Bacciu, Alessio Micheli, Marco Podda
Graph generation with Machine Learning is an open problem with applications in various research fields.
2 code implementations • 29 Dec 2019 • Davide Bacciu, Federico Errica, Alessio Micheli, Marco Podda
The adaptive processing of graph data is a long-standing research topic which has been lately consolidated as a theme of major interest in the deep learning community.
4 code implementations • ICLR 2020 • Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli
We believe that this work can contribute to the development of the graph learning field, by providing a much needed grounding for rigorous evaluations of graph classification models.
Ranked #1 on Graph Classification on REDDIT-MULTI-5k