Publications

• Neurodiversity Meets Colors: Does Position Awareness Destroy Generalization in Brain Graph Learning?

M A Pereira Dantas, Caterina Graziani, L S Ferraz Ribeiro, A C Ponce de Leon Ferreira de Carvalho

ICLR 2026 GRaM Workshop

⭐️ Part of an invited talk at the UiT, Tromsø, Norway.

• Rademacher Meets Colors: More Expressivity, but at What Cost?

M Carrasco*, C Netto*, V A Martirosyan*, A Mehrab*, E Okoyomon*, C Graziani

NeurIPS 2025 NPGML Workshop

⭐️ Invited talk at the Department of Mathematics “Tullio-Levi-Civita”, Padua, Italy.

⭐️ Part of an invited talk at the UiT, Tromsø, Norway.

• The Expressive Power of Path-based Graph Neural Networks

C Graziani*, T Drucks*, F Jogl, M Bianchini, F Scarselli, T Gärtner

In the Forty-first International Conference of Machine Learning (ICML), 2024

• Point-Wise Ribosome Translation Speed Prediction with Recurrent Neural Networks

P Bongini, N Pancino, V Lachi, C Graziani, G Giacomini, P Andreini, M Bianchini 

Mathematics 12, 3, 2024

• Weisfeiler–Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs

S Beddar-Wiesing*, GA D’Inverno*, C Graziani*, V Lachi*, A Moallemy-Oureh*, F Scarselli, JM Thomas.

Neural Networks, Volume 173, 2024

• NO PAIN NO GAIN: Expressive GNNs with Path Aggregation

C Graziani*, T Drucks*, M Bianchini, F Scarselli, T Gärtner

NeurIPS 2023 GLFrontiers Workshop

• Enhancing Embedding Representations of Biomedical Data using Logic Knowledge

M Diligenti, F Giannini, S Fioravanti, C Graziani, M Falaschi, G Marra

In the International Joint Conference on Neural Networks (IJCNN) 2023

• On the Extension of theWeisfeiler-Lehman Hierarchy by WL Tests for Arbitrary Graphs

S Beddar-Wiesing*, GA D’Inverno*, C Graziani*, V Lachi*, A Moallemy-Oureh*, F Scarselli.

MLG Workshop - ECMLPKDD 2022

• Multi-stage Synthetic Image Generation for the Semantic Segmentation of Medical Images

P Andreini, S Bonechi, G Ciano, C Graziani, V Lachi, N Nikoloulopoulou, M Bianchini, F Scarselli

In Artificial Intelligence and Machine Learning for Healthcare (pp. 79-104).

• A Neural Network Approach for the Analysis of Reproducible Ribo–Seq Profiles

G Giacomini*, C Graziani*, V Lachi*, P Bongini*, N Pancino*, M Bianchini, D Chiarugi, A Valleriani, P Andreini*

Algorithms, 15(8) [10.3390/a15080274].

• Blinking Rate Comparison Between Patients with Chronic Pain and Parkinson’s Disease

E Stefanescu, N Pancino, C Graziani, V Lachi, M Sampoli, G Dimitri, A Bargagli, D Zanca, M Bianchini, D Muresanu,  A Rufa

European Journal of Neurology 29, 669-669, 2022.

• A mixed statistical and machine learning approach for the analysis of multimodal trail-making test data

N Pancino*, C Graziani*, V Lachi*, ML Sampoli, E Stefanescu, M Bianchini, GM Dimitri*

Mathematics 9, 3159, 2021.

• A Two-Stage GAN for High-Resolution Retinal Image Generation and Segmentation

P Andreini, G Ciano, S Bonechi, C Graziani, V Lachi, A Mecocci, A Sodi, F Scarselli, M Bianchini

Electronics 11, 60, 2021.