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Federico Barbero
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2020 – today
- 2024
- [c5]Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni:
Locality-Aware Graph Rewiring in GNNs. ICLR 2024 - [i10]Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein:
Bundle Neural Networks for message diffusion on graphs. CoRR abs/2405.15540 (2024) - [i9]Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João G. M. Araújo, Alex Vitvitskyi, Razvan Pascanu, Petar Velickovic:
Transformers need glasses! Information over-squashing in language tasks. CoRR abs/2406.04267 (2024) - [i8]Petar Velickovic, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu:
softmax is not enough (for sharp out-of-distribution). CoRR abs/2410.01104 (2024) - [i7]Federico Barbero, Alex Vitvitskyi, Christos Perivolaropoulos, Razvan Pascanu, Petar Velickovic:
Round and Round We Go! What makes Rotary Positional Encodings useful? CoRR abs/2410.06205 (2024) - 2023
- [c4]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. ICLR 2023 - [c3]Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML 2023: 7865-7885 - [i6]Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio', Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. CoRR abs/2302.02941 (2023) - [i5]Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni:
Locality-Aware Graph-Rewiring in GNNs. CoRR abs/2310.01668 (2023) - 2022
- [c2]Federico Barbero, Feargus Pendlebury, Fabio Pierazzi
, Lorenzo Cavallaro
Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift. SP 2022: 805-823 - [c1]Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò:
Sheaf Neural Networks with Connection Laplacians. TAG-ML 2022: 28-36 - [i4]Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò
Sheaf Neural Networks with Connection Laplacians. CoRR abs/2206.08702 (2022) - [i3]Haitz Sáez de Ocáriz Borde, Federico Barbero:
Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression. CoRR abs/2209.13410 (2022) - [i2]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. CoRR abs/2211.16199 (2022) - 2020
- [i1]Federico Barbero, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Transcending Transcend: Revisiting Malware Classification with Conformal Evaluation. CoRR abs/2010.03856 (2020)
Coauthor Index
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