A Systematic Assessment of Deep Learning Models for Molecule Generation. - Davide Rigoni 001; Nicolò Navarin; Alessandro Sperduti (ESANN, 2020)

Conditional Constrained Graph Variational Autoencoders for Molecule Design. - Davide Rigoni 001; Nicolò Navarin; Alessandro Sperduti (SSCI, 2020)

A better loss for visual-textual grounding. - Davide Rigoni 001; Luciano Serafini; Alessandro Sperduti (SAC, 2022)

Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement. - Davide Rigoni 001; Luca Parolari; Luciano Serafini; Alessandro Sperduti; Lamberto Ballan (BMVC, 2023)

Cleaner Categories Improve Object Detection and Visual-Textual Grounding. - Davide Rigoni 001; Desmond Elliott; Stella Frank (SCIA (1), 2023)

Prompt-Based Data Augmentation Using Contrastive Learning Under Scarcity of Annotated Data. - Muhammad Uzair-Ul-Haq; Davide Rigoni 001; Alessandro Sperduti (ECAI, 2024)

Object search by a concept-conditioned object detector. - Davide Rigoni 001; Luciano Serafini; Alessandro Sperduti (Neural Comput. Appl., 2024)

RGCVAE: relational graph conditioned variational autoencoder for molecule design. - Davide Rigoni 001; Nicolò Navarin; Alessandro Sperduti (Mach. Learn., 2025)

LLMs as Data Annotators: How Close Are We to Human Performance. - Muhammad Uzair-Ul-Haq; Davide Rigoni 001; Alessandro Sperduti (CoRR, 2025)