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Viewing Publication 1 - 39 from 39

2025

RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone DesignRishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian Rokkum Jamasb, Charles Harris, Simon V. Mathis, Kieran Didi, Rex Ying, Bryan Hooi, Pietro Lio. tmlr, 2025, 2025. [doi]

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential EquationsRichard Bergna, Sergio Calvo-Ordoñez, Felix L. Opolka, Pietro Lio, José Miguel Hernández-Lobato. iclr 2025: [doi]

SynFlowNet: Design of Diverse and Novel Molecules with Synthesis ConstraintsMiruna T. Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Bruno E. Correia, Julien Roy, Emmanuel Bengio, Pietro Lio. iclr 2025: [doi]

Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training ProcessingMd Mehedi Hasan, Moloud Abdar, Abbas Khosravi, Uwe Aickelin, Pietro Lio, Ibrahim Hossain, Ashikur Rahman, Saeid Nahavandi. ACM Comput. Surv., 57(9), September 2025. [doi]

gRNAde: Geometric Deep Learning for 3D RNA inverse designChaitanya K. Joshi, Arian Rokkum Jamasb, Ramón Viñas Torné 0001, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Lio. iclr 2025: [doi]

Decoding the Stressed Brain with Geometric Machine LearningSonia Koszut, Sam Nallaperuma Herzberg, Pietro Lio. aiih 2026: 3-16 [doi]

Explaining the Explainers in Graph Neural Networks: a Comparative StudyAntonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Lio, Bruno Lepri, Andrea Passerini. ACM Comput. Surv., 57(5), May 2025. [doi]

Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networksMichail Mamalakis, Antonios Mamalakis, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Graham K. Murray, John Suckling, Pietro Lio. aiopen, 6:70-81, 2025. [doi]

Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture DesignLev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernárdez, Olga Zaghen, Simone Scardapane, Pietro Lio. tmlr, 2025, 2025. [doi]

Research on Privacy Protection Technology of "2+2" Verifiable Federated LearningPan Wang, Xiaofeng Lu, Pietro Lio. iotj, 12(13):24094-24103, July 2025. [doi]

EARVP: Efficient Aggregation for Federated Learning With Robustness, Verifiability, and PrivacyCaihong Yan, Xiaofeng Lu, Pietro Lio, Pan Hui 0001. tifs, 20:5936-5951, 2025. [doi]

Self-Simulation and Meta-Model Aggregation-Based Heterogeneous-Graph-Coupled Federated LearningCaihong Yan, Xiaofeng Lu, Pietro Lio, Pan Hui 0001, Daojing He. iotj, 12(1):198-212, jan1 2025. [doi]

2024

HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed HypergraphsAdrián Bazaga, Pietro Lio, Gos Micklem. emnlp 2024: 9181-9193 [doi]

Unsupervised Pretraining for Fact Verification by Language Model DistillationAdrián Bazaga, Pietro Lio, Gos Micklem. iclr 2024: [doi]

Language Model Knowledge Distillation for Efficient Question Answering in SpanishAdrián Bazaga, Pietro Lio, Gos Micklem. iclr 2024: [doi]

How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashingKeke Huang, Yu Guang Wang 0001, Ming Li 0065, Pietro Lio. icml 2024: [doi]

Evaluating Representation Learning on the Protein Structure UniverseArian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang 0005, Jianlin Cheng, Pietro Lio, Tom L. Blundell. iclr 2024: [doi]

Dynamics-Informed Protein Design with Structure ConditioningUrszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas 0001, Pietro Lio, Mateja Jamnik. iclr 2024: [doi]

SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN networkXiaofeng Lu, Jinglun Zhao, Senhao Zhu, Pietro Lio. eswa, 250:123922, 2024. [doi]

xAI-Drop: Don't Use What You Cannot ExplainVincenzo Marco De Luca, Antonio Longa, Pietro Lio, Andrea Passerini. log 2024: 16 [doi]

GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular DataAndrei Margeloiu, Nikola Simidjievski, Pietro Lio, Mateja Jamnik. tmlr, 2024, 2024. [doi]

Deep Kernel Learning of Nonlinear Latent Force ModelsJacob Moss, Jeremy L. England, Pietro Lio. tmlr, 2024, 2024. [doi]

Structure-based drug design with equivariant diffusion modelsArne Schneuing, Charles Harris, Yuanqi Du, Kieran Didi, Arian Rokkum Jamasb, Ilia Igashov, Weitao Du, Carla P. Gomes, Tom L. Blundell, Pietro Lio, Max Welling, Michael M. Bronstein, Bruno E. Correia. ncs, 4(12):899-909, December 2024. [doi]

2023

Interpretable Neural-Symbolic Concept ReasoningPietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra. icml 2023: 1801-1825 [doi]

DBGSL: Dynamic Brain Graph Structure LearningAlexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio. midl 2023: 1318-1345 [doi]

DBGDGM: Dynamic Brain Graph Deep Generative ModelAlexander Campbell, Simeon Emilov Spasov, Nicola Toschi, Pietro Lio. midl 2023: 1346-1371 [doi]

StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI imagesAnjir Ahmed Chowdhury, S. M. Hasan Mahmud, Khadija Kubra Shahjalal Hoque, Kawsar Ahmed, Francis M. Bui, Pietro Lio, Mohammad Ali Moni, Fahad Ahmed Al-Zahrani. jksucis, 35(8):101647, September 2023. [doi]

Learning Logic Explanations by Neural NetworksGabriele Ciravegna, Francesco Giannini, Pietro Barbiero, Marco Gori, Pietro Lio, Marco Maggini, Stefano Melacci. In Pascal Hitzler, Md. Kamruzzaman Sarker, Aaron Eberhart, editors, Compendium of Neurosymbolic Artificial Intelligence. Volume 369 of Frontiers in Artificial Intelligence and Applications, pages 547-558, IOS Press, 2023. [doi]

Neural Algorithmic Reasoning for Combinatorial OptimisationDobrik Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio. log 2023: 28 [doi]

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and TopologyFrancesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein. icml 2023: 7865-7885 [doi]

On the Expressive Power of Geometric Graph Neural NetworksChaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio. icml 2023: 15330-15355 [doi]

Bridging Equational Properties and Patterns on Graphs: an AI-Based ApproachOguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini. tagml 2023: 156-168 [doi]

Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and OpportunitiesAntonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Lio, Franco Scarselli, Andrea Passerini. tmlr, 2023, 2023. [doi]

RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine LearningXiaofeng Lu, Chao Liu, Senhao Zhu, Yilu Mao, Pietro Lio, Pan Hui 0001. tpds, 34(12):3266-3279, December 2023. [doi]

A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation LearningZhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio. bigdataconf 2023: 5930-5939 [doi]

Adaptive Distance Message Passing From the Multi-Relational Edge ViewZhongtian Sun, Alexandra I. Cristea, Pietro Lio, Jialin Yu. iclr 2023: [doi]

MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph modelZhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio. aiopen, 4:165-174, January 2023. [doi]

Will More Expressive Graph Neural Networks Do Better on Generative Tasks?Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao. log 2023: 21 [doi]

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