Marco Podda

Proceedings of the Explainable Artificial Intelligence, 2024

Classifier-Free Graph Diffusion for Molecular Property Targeting.

[BibT_eX]

[DOI]

Matteo Ninniri

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

How Much Do DNA and Protein Deep Embeddings Preserve Biological Information?

[BibT_eX]

[DOI]

Proceedings of the Computational Methods in Systems Biology, 2024

2023

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs.

[BibT_eX]

[DOI]

Bioinform., October, 2023

Biochemical networks with simulation-based estimations of dynamical properties.

[BibT_eX]

[DOI]

Dataset, June, 2023

Graph Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

2021

Deep Learning on Graphs with Applications to the Life Sciences.

[BibT_eX]

[DOI]

PhD thesis, 2021

Graphgen-redux: a Fast and Lightweight Recurrent Model for labeled Graph Generation.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

A gentle introduction to deep learning for graphs.

[BibT_eX]

[DOI]

Neural Networks, 2020

Edge-based sequential graph generation with recurrent neural networks.

[BibT_eX]

[DOI]

Neurocomputing, 2020

A Fair Comparison of Graph Neural Networks for Graph Classification.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Biochemical Pathway Robustness Prediction with Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Classification of Biochemical Pathway Robustness with Neural Networks for Graphs.

[BibT_eX]

[DOI]

Proceedings of the Biomedical Engineering Systems and Technologies, 2020

Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020), 2020

A Deep Generative Model for Fragment-Based Molecule Generation.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Graph generation by sequential edge prediction.

[BibT_eX]

[DOI]