Federico Errica
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
6
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ESANN | Foundation and Generative Models for Graphs. | Davide Bacciu, Federico Errica, Stefano Moro, Luca Pasa, Davide Rigoni, Daniele Zambon |
| 2025 | ICML | Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching. | Federico Errica, Henrik Christiansen, Viktor Zaverkin, Takashi Maruyama, Mathias Niepert, Francesco Alesiani |
| 2025 | NAACL | What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering. | Federico Errica, Davide Sanvito, Giuseppe Siracusano, Roberto Bifulco |
| 2024 | ICLR | Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks. | Federico Errica, Mathias Niepert |
| 2024 | IJCAI | History Repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting. | Julia Gastinger, Christian Meilicke, Federico Errica, Timo Sztyler, Anett Schlke, Heiner Stuckenschmidt |
| 2023 | ESANN | Graph Representation Learning. | Davide Bacciu, Federico Errica, Alessio Micheli, Nicol Navarin, Luca Pasa, Marco Podda, Daniele Zambon |
| 2023 | ESANN | Hidden Markov Models for Temporal Graph Representation Learning. | Federico Errica, Alessio Gravina, Davide Bacciu, Alessio Micheli |
| 2022 | ESANN | Deep Learning for Graphs. | Davide Bacciu, Federico Errica, Nicol Navarin, Luca Pasa, Daniele Zambon |
| 2022 | ICML | The Infinite Contextual Graph Markov Model. | Daniele Castellana, Federico Errica, Davide Bacciu, Alessio Micheli |
| 2021 | ESANN | Robust Malware Classification via Deep Graph Networks on Call Graph Topologies. | Federico Errica, Giacomo Iadarola, Fabio Martinelli, Francesco Mercaldo, Alessio Micheli |
| 2021 | ESANN | Complex Data: Learning Trustworthily, Automatically, and with Guarantees. | Luca Oneto, Nicol Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti |
| 2021 | ICML | Graph Mixture Density Networks. | Federico Errica, Davide Bacciu, Alessio Micheli |
| 2021 | IJCNN | Modeling Edge Features with Deep Bayesian Graph Networks. | Daniele Atzeni, Davide Bacciu, Federico Errica, Alessio Micheli |
| 2021 | IJCNN | Concept Matching for Low-Resource Classification. | Federico Errica, Fabrizio Silvestri, Bora Edizel, Ludovic Denoyer, Fabio Petroni, Vassilis Plachouras, Sebastian Riedel |
| 2020 | ESANN | Theoretically Expressive and Edge-aware Graph Learning. | Federico Errica, Davide Bacciu, Alessio Micheli |
| 2020 | ICLR | A Fair Comparison of Graph Neural Networks for Graph Classification. | Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli |
| 2018 | ICML | Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing. | Davide Bacciu, Federico Errica, Alessio Micheli |