Simulation-Based Evolutionary Optimization of Air Traffic Management. - Alessandro Pellegrini 001; Pierangelo di Sanzo; Beatrice Bevilacqua; Gabriella Duca; Domenico Pascarella; Roberto Palumbo; Juan José Ramos; Miquel Angel Piera; Gabriella Gigante (IEEE Access, 2020)

Size-Invariant Graph Representations for Graph Classification Extrapolations. - Beatrice Bevilacqua; Yangze Zhou; Bruno Ribeiro 001 (ICML, 2021)

Equivariant Subgraph Aggregation Networks. - Beatrice Bevilacqua; Fabrizio Frasca; Derek Lim; Balasubramaniam Srinivasan; Chen Cai; Gopinath Balamurugan; Michael M. Bronstein; Haggai Maron (ICLR, 2022)

A Generalist Neural Algorithmic Learner. - Borja Ibarz; Vitaly Kurin; George Papamakarios; Kyriacos Nikiforou; Mehdi Bennani; Róbert Csordás; Andrew Joseph Dudzik; Matko Bosnjak; Alex Vitvitskyi; Yulia Rubanova; Andreea Deac; Beatrice Bevilacqua; et al. (LoG, 2022)

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. - Fabrizio Frasca; Beatrice Bevilacqua; Michael M. Bronstein; Haggai Maron (NeurIPS, 2022)

Neural Algorithmic Reasoning with Causal Regularisation. - Beatrice Bevilacqua; Kyriacos Nikiforou; Borja Ibarz; Ioana Bica; Michela Paganini; Charles Blundell; Jovana Mitrovic; Petar Velickovic (ICML, 2023)

Graph Positional Encoding via Random Feature Propagation. - Moshe Eliasof; Fabrizio Frasca; Beatrice Bevilacqua; Eran Treister; Gal Chechik; Haggai Maron (ICML, 2023)

Causal Lifting and Link Prediction. - Leonardo Cotta; Beatrice Bevilacqua; Nesreen Ahmed; Bruno Ribeiro 001 (CoRR, 2023)

An OOD Multi-Task Perspective for Link Prediction with New Relation Types and Nodes. - Jincheng Zhou; Beatrice Bevilacqua; Bruno Ribeiro 001 (CoRR, 2023)

Efficient Subgraph GNNs by Learning Effective Selection Policies. - Beatrice Bevilacqua; Moshe Eliasof; Eli A. Meirom; Bruno Ribeiro 001; Haggai Maron (ICLR, 2024)

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products. - Guy Bar-Shalom; Beatrice Bevilacqua; Haggai Maron (ICML, 2024)

TRIX: A More Expressive Model for Zero-Shot Domain Transfer in Knowledge Graphs. - Yucheng Zhang; Beatrice Bevilacqua; Mikhail Galkin 001; Bruno Ribeiro 001 (LoG, 2024)

GRANOLA: Adaptive Normalization for Graph Neural Networks. - Moshe Eliasof; Beatrice Bevilacqua; Carola-Bibiane Schönlieb; Haggai Maron (NeurIPS, 2024)

DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. - Krishna Sri Ipsit Mantri; Xinzhi Wang; Carola-Bibiane Schönlieb; Bruno Ribeiro 001; Beatrice Bevilacqua; Moshe Eliasof (NeurIPS, 2024)

Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings. - Beatrice Bevilacqua; Joshua Robinson 001; Jure Leskovec; Bruno Ribeiro 001 (ICLR, 2025)

On the Effectiveness of Random Weights in Graph Neural Networks. - Thu Bui; Carola-Bibiane Schönlieb; Bruno Ribeiro 001; Beatrice Bevilacqua; Moshe Eliasof (CoRR, 2025)

Boosting Relational Deep Learning with Pretrained Tabular Models. - Veronica Lachi; Antonio Longa; Beatrice Bevilacqua; Bruno Lepri; Andrea Passerini; Bruno Ribeiro 001 (CoRR, 2025)