Lorenzo Bini

According to our database, Lorenzo Bini authored at least 10 papers between 2024 and 2026.

Collaborative distances:

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

2026

Embedded Rust or C Firmware? Lessons from an Industrial Microcontroller Use Case with Ariel OS.

Bipin Thapa, Daniele Alfonso, Lorenzo Bini, Licio Mapelli, Kaspar Schleiser, Romain Fouquet, Emmanuel Baccelli

CoRR, April, 2026

Probing Graph Neural Network Activation Patterns Through Graph Topology.

Floriano Tori, Lorenzo Bini, Marco Sorbi, Stéphane Marchand-Maillet, Vincent Ginis

CoRR, February, 2026

2025

Self-Supervised Graph Learning via Spectral Bootstrapping and Laplacian-Based Augmentations.

Lorenzo Bini, Stéphane Marchand-Maillet

CoRR, June, 2025

LapDDPM: A Conditional Graph Diffusion Model for scRNA-seq Generation with Spectral Adversarial Perturbations.

Lorenzo Bini, Stéphane Marchand-Maillet

CoRR, June, 2025

Massive Activations in Graph Neural Networks: Decoding Attention dor Domain-Dependent Interpretability.

Lorenzo Bini, Marco Sorbi, Stéphane Marchand-Maillet

Proceedings of the Second Workshop on Second Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2025) co-located with 28th European Conference on Artificial Intelligence (ECAI 2025), 2025

2024

Characterizing Massive Activations of Attention Mechanism in Graph Neural Networks.

Lorenzo Bini, Marco Sorbi, Stéphane Marchand-Maillet

CoRR, 2024

Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction.

Fatemeh Nassajian Mojarrad, Lorenzo Bini, Thomas Matthes, Stéphane Marchand-Maillet

CoRR, 2024

HemaGraph: Breaking Barriers in Hematologic Single Cell Classification with Graph Attention.

Lorenzo Bini, Fatemeh Nassajian Mojarrad, Thomas Matthes, Stéphane Marchand-Maillet

CoRR, 2024

Why Attention Graphs Are All We Need: Pioneering Hierarchical Classification of Hematologic Cell Populations with LeukoGraph.

Fatemeh Nassajian Mojarrad, Lorenzo Bini, Thomas Matthes, Stéphane Marchand-Maillet

CoRR, 2024

FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking.

Lorenzo Bini, Fatemeh Nassajian Mojarrad, Margarita Liarou, Thomas Matthes, Stéphane Marchand-Maillet

Proceedings of the Conference on Health, 2024