Suivre
Federico Barbero
Titre
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Année
On over-squashing in message passing neural networks: The impact of width, depth, and topology
F Di Giovanni, L Giusti, F Barbero, G Luise, P Lio, M Bronstein
International Conference on Machine Learning (ICML 2023), 2023
139*2023
Transcending transcend: Revisiting malware classification with conformal evaluation
F Barbero, F Pendlebury, F Pierazzi, L Cavallaro
2022 IEEE Symposium on Security and Privacy, 1332-1349, 2022
98*2022
Sheaf neural networks with connection laplacians
F Barbero, C Bodnar, HS de Ocáriz Borde, M Bronstein, P Veličković, ...
Topological, Algebraic and Geometric Learning Workshops 2022, 28-36, 2022
482022
Latent Graph Inference using Product Manifolds
HS de Ocáriz Borde, A Kazi, F Barbero, P Lio
International Conference on Learning Representations (ICLR 2023), 2023
26*2023
Sheaf attention networks
F Barbero, C Bodnar, HS de Ocáriz Borde, P Lio
NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022
262022
Locality-aware graph-rewiring in gnns
F Barbero, A Velingker, A Saberi, M Bronstein, F Di Giovanni
International Conference on Learning Representations (ICLR 2024), 2024
232024
Transformers need glasses! Information over-squashing in language tasks
F Barbero, A Banino, S Kapturowski, D Kumaran, JGM Araújo, A Vitvitskyi, ...
Advances in Neural Information Processing Systems (NeurIPS 2024), 2024
132024
Round and Round We Go! What makes Rotary Positional Encodings useful?
F Barbero, A Vitvitskyi, C Perivolaropoulos, R Pascanu, P Veličković
International Conference on Learning Representations (ICLR 2025), 2025
62025
Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression
HS de Ocáriz Borde, F Barbero
The First Learning on Graphs Conference, 2022
22022
Scalable emulation of protein equilibrium ensembles with generative deep learning
S Lewis, T Hempel, J Jiménez Luna, M Gastegger, Y Xie, AYK Foong, ...
bioRxiv, 2024.12. 05.626885, 2024
12024
Bundle Neural Networks for message diffusion on graphs
J Bamberger, F Barbero, X Dong, M Bronstein
International Conference on Learning Representations (ICLR 2025) Spotlight, 2025
2025
Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification
BA Tjandra, F Barbero, M Bronstein
arXiv preprint arXiv:2411.03596, 2024
2024
softmax is not enough (for sharp out-of-distribution)
P Veličković, C Perivolaropoulos, F Barbero, R Pascanu
arXiv preprint arXiv:2410.01104, 2024
2024
Attention-based Sheaf Neural Networks
F Barbero
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