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pietro.lio@uniroma1.it
Pietro Lio
Professore Ordinario
Struttura:
DIPARTIMENTO DI INGEGNERIA INFORMATICA, AUTOMATICA E GESTIONALE -ANTONIO RUBERTI-
E-mail:
pietro.lio@uniroma1.it
Pagina istituzionale corsi di laurea
Curriculum Sapienza
Pubblicazioni
Titolo
Pubblicato in
Anno
gRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design
Methods in Molecular Biology
2025
A conditional protein diffusion model generates artificial programmable endonuclease sequences with enhanced activity
CELL DISCOVERY
2024
Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting
NATURE COMMUNICATIONS
2024
Intratumoral antigen signaling traps CD8+ T cells to confine exhaustion to the tumor site
SCIENCE IMMUNOLOGY
2024
Adaptive multi-scale Graph Neural Architecture Search framework
NEUROCOMPUTING
2024
Self-simulation and Meta-Model Aggregation Based Heterogeneous Graph Coupled Federated Learning
IEEE INTERNET OF THINGS JOURNAL
2024
Dual-stream multi-dependency graph neural network enables precise cancer survival analysis
MEDICAL IMAGE ANALYSIS
2024
Elegans-AI: How the connectome of a living organism could model artificial neural networks
NEUROCOMPUTING
2024
Leveraging graph neural networks for supporting automatic triage of patients
SCIENTIFIC REPORTS
2024
Graph Rewiring and Preprocessing for Graph Neural Networks Based on Effective Resistance
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
2024
On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering
FARADAY DISCUSSIONS
2024
SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN network
EXPERT SYSTEMS WITH APPLICATIONS
2024
Using AI explainable models and handwriting/drawing tasks for psychological well-being
INFORMATION SYSTEMS
2024
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2024
Position: Topological Deep Learning is the New Frontier for Relational Learning
Proceedings of Machine Learning Research
2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Proceedings of Machine Learning Research
2024
Denoising Probabilistic Diffusion Models for Synthetic Healthcare Image Generation
2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024 - Proceedings
2024
Categorical Foundation of Explainable AI: A Unifying Theory
Communications in Computer and Information Science
2024
State of the Art and Potentialities of Graph-level Learning
ACM COMPUTING SURVEYS
2024
LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond[Formula presented]
SOFTWARE IMPACTS
2024
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