Maria Sofia Bucarelli

According to our database, Maria Sofia Bucarelli authored at least 14 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A topological description of loss surfaces based on Betti Numbers.

Maria Sofia Bucarelli, Giuseppe Alessio D'Inverno, Monica Bianchini, Franco Scarselli, Fabrizio Silvestri

Neural Networks, 2024

Robustness of Graph Classification: failure modes, causes, and noise-resistant loss in Graph Neural Networks.

Farooq Ahmad Wani, Maria Sofia Bucarelli, Andrea Giuseppe Di Francesco, Oleksandr Pryymak, Fabrizio Silvestri

CoRR, 2024

Task Singular Vectors: Reducing Task Interference in Model Merging.

Antonio Andrea Gargiulo, Donato Crisostomi, Maria Sofia Bucarelli, Simone Scardapane, Fabrizio Silvestri, Emanuele Rodolà

CoRR, 2024

ATM: Improving Model Merging by Alternating Tuning and Merging.

Luca Zhou, Daniele Solombrino, Donato Crisostomi, Maria Sofia Bucarelli, Fabrizio Silvestri, Emanuele Rodolà

CoRR, 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.

Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane

CoRR, 2024

∇ τ: Gradient-based and Task-Agnostic machine Unlearning.

Daniel Trippa, Cesare Campagnano, Maria Sofia Bucarelli, Gabriele Tolomei, Fabrizio Silvestri

CoRR, 2024

Link Prediction under Heterophily: A Physics-Inspired Graph Neural Network Approach.

Andrea Giuseppe Di Francesco, Francesco Caso, Maria Sofia Bucarelli, Fabrizio Silvestri

CoRR, 2024

Learning with Noisy Labels through Learnable Weighting and Centroid Similarity.

Farooq Ahmad Wani, Maria Sofia Bucarelli, Fabrizio Silvestri

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

False Data Injection Impact on High RES Power Systems with Centralized Voltage Regulation Architecture.

Tommaso Bragatto, Marco Antonio Bucarelli, Maria Sofia Bucarelli, Federico Carere, Alberto Geri, Marco Maccioni

Sensors, March, 2023

Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design.

Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernárdez, Olga Zaghen, Simone Scardapane, Pietro Lio

CoRR, 2023

Combining Distance to Class Centroids and Outlier Discounting for Improved Learning with Noisy Labels.

Farooq Ahmad Wani, Maria Sofia Bucarelli, Fabrizio Silvestri

CoRR, 2023

On Generalization Bounds for Projective Clustering.

Maria Sofia Bucarelli, Matilde Fjeldsø Larsen, Chris Schwiegelshohn, Mads Toftrup

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels.

Maria Sofia Bucarelli, Lucas Cassano, Federico Siciliano, Amin Mantrach, Fabrizio Silvestri

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks.

Federico Siciliano, Maria Sofia Bucarelli, Gabriele Tolomei, Fabrizio Silvestri

Proceedings of the International Joint Conference on Neural Networks, 2022