Pietro Lio - RankMe

95 papers A* 19B 1C 1Journal 61Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Monosemantic Attribution Framework for Stable Interpretability in Clinical Neuroscience Large Language Models. CoRR Michail Mamalakis, Tiago Azevedo, Cristian Cosentino, Chiara D'Ercoli, Subati Abulikemu, Zhongtian Sun, Richard A. I. Bethlehem, Pietro Lio
2026	J	`jnl`	A Survey on Over-smoothing and Over-squashing: Unified Propagation Perspectives on Graph Neural Networks and Transformers. Trans. Mach. Learn. Res. Alvaro Arroyo, Federico Barbero, Hugh Blayney, Michael M. Bronstein, Xiaowen Dong, Pietro Lio, Razvan Pascanu, Pierre Vandergheynst
2026	J	`jnl`	An explainable three dimensional framework to uncover learning patterns: A unified look in variable sulci recognition. Artif. Intell. Medicine Michail Mamalakis, Héloïse de Vareilles, Atheer Al-Manea, Samantha C. Mitchell, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Jane R. Garrison, Jon S. Simons, Pietro Lio, John Suckling, Graham K. Murray
2026	J	`jnl`	Assessment of transformer-based AI in clinical oncology. BMC Medical Informatics Decis. Mak. Lim Weng Seong, Pietro Lio, Nur Aishah Taib, Mogana Darshini Ganggayah, Sarinder Kaur Dhillon
2026	J	`jnl`	DVFL: A Lightweight Verifiable Federated Learning System With Dynamic Obfuscation for Resource-Constrained IoT Devices. IEEE Internet Things J. Pan Wang, Xiaofeng Lu, Chaoyi Bian, Pietro Lio
2026	A*	`conf`	High-Pass Matters: Theoretical Insights and Sheaflet-Based Design for Hypergraph Neural Networks. AAAI Ming Li, Yujie Fang, Dongrui Shen, Han Feng, Xiaosheng Zhuang, Kelin Xia, Pietro Lio
2026	J	`jnl`	MODE: Efficient Time Series Prediction with Mamba Enhanced by Low-Rank Neural ODEs. CoRR Xingsheng Chen, Regina Zhang, Bo Gao, Xingwei He, Xiaofeng Liu, Pietro Lio, Kwok-Yan Lam, Siu-Ming Yiu
2026	J	`jnl`	Molecular Representations in Implicit Functional Space via Hyper-Networks. CoRR Zehong Wang, Xiaolong Han, Qi Yang, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye
2026	J	`jnl`	Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding. CoRR Rishabh Jain, Keisuke Okumura, Michael Amir, Pietro Lio, Amanda Prorok
2026	A*	`conf`	Permutation Equivariant Framelet-based Hypergraph Neural Networks. AAAI Ming Li, Yi Wang, Chengling Gao, Lu Bai, Yujie Fang, Xiaosheng Zhuang, Pietro Lio
2026	J	`jnl`	Position Encoding-Enhanced Adaptive Expansion Graph Attention Network for Anomaly Detection in Multivariate Time Series. IEEE Internet Things J. Xiaoyu Zhang, Xiaofeng Lu, Yaru Zhao, Pietro Lio, Pan Hui
2026	J	`jnl`	RPCE: Dynamic Data Replicas Placement Management by Cloud and Edge Collaboration. IEEE Trans. Parallel Distributed Syst. Xiaofeng Lu, Luwen Zou, Yilu Mao, Pietro Lio, Pan Hui
2026	J	`jnl`	RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis. CoRR Chris Tomy, Mo Vali, David Pertzborn, Tammam Alamatouri, Anna Mühlig, Orlando Guntinas-Lichius, Anna Xylander, Eric Michele Fantuzzi, Matteo Negro, Francesco Crisafi, Pietro Lio, Tiago Azevedo
2026	J	`jnl`	TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality. Trans. Mach. Learn. Res. Carlos Vonessen, Charles Harris, Miruna T. Cretu, Pietro Lio
2026	J	`jnl`	Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials. CoRR Alex Morehead, Miruna T. Cretu, Antonia Panescu, Rishabh Anand, Maurice Weiler, Tynan Perez, Samuel M. Blau, Steven Farrell, Wahid Bhimji, Anubhav Jain, Hrushikesh Sahasrabuddhe, Pietro Lio, Tommi S. Jaakkola, Rafael Gómez-Bombarelli, Rex Ying, N. Benjamin Erichson, Michael W. Mahoney
2025	J	`jnl`	A Comprehensive Survey on Benchmarks and Solutions in Software Engineering of LLM-Empowered Agentic System. CoRR Jiale Guo, Suizhi Huang, Mei Li, Dong Huang, Xingsheng Chen, Regina Zhang, Zhijiang Guo, Han Yu, Siu-Ming Yiu, Pietro Lio, Kwok-Yan Lam
2025	J	`jnl`	Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning. CoRR Zhongtian Sun, Anoushka Harit, Pietro Lio
2025	J	`jnl`	Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo. CoRR Cheuk Kit Lee, Paul Jeha, Jes Frellsen, Pietro Lio, Michael Samuel Albergo, Francisco Vargas
2025	—	`conf`	Decoding the Stressed Brain with Geometric Machine Learning. AIiH (2) Sonia Koszut, Sam Nallaperuma Herzberg, Pietro Lio
2025	J	`jnl`	Decoding the Stressed Brain with Geometric Machine Learning. CoRR Sonia Koszut, Sam Nallaperuma Herzberg, Pietro Lio
2025	J	`jnl`	Deep Spectral Prior. CoRR Yanqi Cheng, Tieyong Zeng, Pietro Lio, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero
2025	J	`jnl`	EARVP: Efficient Aggregation for Federated Learning With Robustness, Verifiability, and Privacy. IEEE Trans. Inf. Forensics Secur. Caihong Yan, Xiaofeng Lu, Pietro Lio, Pan Hui
2025	A*	`conf`	EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction. ICML Ming Li, Yukang Cheng, Lu Bai, Feilong Cao, Ke Lv, Jiye Liang, Pietro Lio
2025	J	`jnl`	Explaining the Explainers in Graph Neural Networks: a Comparative Study. ACM Comput. Surv. Antonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Lio, Bruno Lepri, Andrea Passerini
2025	J	`jnl`	Flows, straight but not so fast: Exploring the design space of Rectified Flows in Protein Design. CoRR Junhua Chen, Simon V. Mathis, Charles Harris, Kieran Didi, Pietro Lio
2025	A*	`conf`	G-Adaptivity: optimised graph-based mesh relocation for finite element methods. ICML James Rowbottom, Georg Maierhofer, Teo Deveney, Eike Hermann Müller, Alberto Paganini, Katharina Schratz, Pietro Lio, Carola-Bibiane Schönlieb, Chris J. Budd
2025	J	`jnl`	Graph Foundation Models: A Comprehensive Survey. CoRR Zehong Wang, Zheyuan Liu, Tianyi Ma, Jiazheng Li, Zheyuan Zhang, Xingbo Fu, Yiyang Li, Zhengqing Yuan, Wei Song, Yijun Ma, Qingkai Zeng, Xiusi Chen, Jianan Zhao, Jundong Li, Meng Jiang, Pietro Lio, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye
2025	A*	`conf`	Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification. ICML Flavio Petruzzellis, Cristina Cornelio, Pietro Lio
2025	J	`jnl`	Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification. CoRR Cristina Cornelio, Flavio Petruzzellis, Pietro Lio
2025	J	`jnl`	How Particle System Theory Enhances Hypergraph Message Passing. CoRR Yixuan Ma, Kai Yi, Pietro Lio, Shi Jin, Yu Guang Wang
2025	J	`jnl`	Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design. Trans. Mach. Learn. Res. Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernárdez, Olga Zaghen, Simone Scardapane, Pietro Lio
2025	—	`conf`	KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis. AAAI Bridge Program Kaiwen Zuo, Yirui Jiang, Fan Mo, Pietro Lio
2025	J	`jnl`	Multi-Level Monte Carlo Training of Neural Operators. CoRR James Rowbottom, Stefania Fresca, Pietro Lio, Carola-Bibiane Schönlieb, Nicolas Boullé
2025	A*	`conf`	NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones. ICML Urszula Julia Komorowska, Francisco Vargas, Alessandro Rondina, Pietro Lio, Mateja Jamnik
2025	J	`jnl`	RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. Trans. Mach. Learn. Res. Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian Rokkum Jamasb, Charles Harris, Simon V. Mathis, Kieran Didi, Rex Ying, Bryan Hooi, Pietro Lio
2025	J	`jnl`	Research on Privacy Protection Technology of "2+2" Verifiable Federated Learning. IEEE Internet Things J. Pan Wang, Xiaofeng Lu, Pietro Lio
2025	A*	`conf`	SPHINX: Structural Prediction using Hypergraph Inference Network. ICML Iulia Duta, Pietro Lio
2025	J	`jnl`	Self-Simulation and Meta-Model Aggregation-Based Heterogeneous-Graph-Coupled Federated Learning. IEEE Internet Things J. Caihong Yan, Xiaofeng Lu, Pietro Lio, Pan Hui, Daojing He
2025	J	`jnl`	Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks. AI Open Michail Mamalakis, Antonios Mamalakis, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Graham K. Murray, John Suckling, Pietro Lio
2025	C	`conf`	Split Learning Privacy Protection Method Based on Differential Computing. ISCC Xiaofeng Lu, Yinghui Li, Pietro Lio
2025	A*	`conf`	Stochastic Encodings for Active Feature Acquisition. ICML Alexander Luke Ian Norcliffe, Changhee Lee, Fergus Imrie, Mihaela van der Schaar, Pietro Lio
2025	J	`jnl`	Stochastic Encodings for Active Feature Acquisition. CoRR Alexander Norcliffe, Changhee Lee, Fergus Imrie, Mihaela van der Schaar, Pietro Lio
2025	J	`jnl`	Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. ACM Comput. Surv. Md. Mehedi Hasan, Moloud Abdar, Abbas Khosravi, Uwe Aickelin, Pietro Lio, Ibrahim Hossain, Ashikur Rahman, Saeid Nahavandi
2025	A*	`conf`	SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints. ICLR Miruna T. Cretu, Charles Harris, Ilia Igashov, Arne Schneuing, Marwin H. S. Segler, Bruno E. Correia, Julien Roy, Emmanuel Bengio, Pietro Lio
2025	J	`jnl`	UESA-Net: U-Shaped Embedded Multidirectional Shrinkage Attention Network for Ultrasound Nodule Segmentation. CoRR Tangqi Shi, Pietro Lio
2025	J	`jnl`	UMP-Net: Uncertainty-Aware Mixture of Prompts Network for Efficient Instruction Tuning. Trans. Mach. Learn. Res. Fatemeh Daneshfar, Abdulhady Abas Abdullah, Moloud Abdar, Pietro Lio
2025	A*	`conf`	Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. ICLR Richard Bergna, Sergio Calvo-Ordoñez, Felix L. Opolka, Pietro Lio, José Miguel Hernández-Lobato
2025	J	`jnl`	Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods. CoRR Carmen Jimenez-Mesa, Yizhou Wan, Guilio Sansone, Francisco Jesús Martínez-Murcia, Javier Ramírez, Pietro Lio, Juan Manuel Górriz, Stephen J. Price, John Suckling, Michail Mamalakis
2025	A*	`conf`	gRNAde: Geometric Deep Learning for 3D RNA inverse design. ICLR Chaitanya K. Joshi, Arian Rokkum Jamasb, Ramón Viñas Torné, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Lio
2024	J	`jnl`	Bayesian Binary Search. CoRR Vikash Singh, Matthew Khanzadeh, Vincent Davis, Harrison Rush, Emanuele Rossi, Jesse Shrader, Pietro Lio
2024	J	`jnl`	Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification. CoRR Michail Mamalakis, Héloïse de Vareilles, Shun-Chin Jim Wu, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Jane R. Garrison, Jon S. Simons, Pietro Lio, John Suckling, Graham K. Murray
2024	J	`jnl`	DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. CoRR Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio
2024	J	`jnl`	Deep Kernel Learning of Nonlinear Latent Force Models. Trans. Mach. Learn. Res. Jacob Moss, Jeremy L. England, Pietro Lio
2024	A*	`conf`	Dynamics-Informed Protein Design with Structure Conditioning. ICLR Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik
2024	A*	`conf`	Evaluating Representation Learning on the Protein Structure Universe. ICLR Arian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom L. Blundell
2024	J	`jnl`	Evaluating representation learning on the protein structure universe. CoRR Arian R. Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V. Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom L. Blundell
2024	J	`jnl`	GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data. Trans. Mach. Learn. Res. Andrei Margeloiu, Nikola Simidjievski, Pietro Lio, Mateja Jamnik
2024	J	`jnl`	GenRec: Generative Personalized Sequential Recommendation. CoRR Panfeng Cao, Pietro Lio
2024	A*	`conf`	How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing. ICML Keke Huang, Yu Guang Wang, Ming Li, Pietro Lio
2024	—	`conf`	HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs. EMNLP (Findings) Adrián Bazaga, Pietro Lio, Gos Micklem
2024	J	`jnl`	KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis. CoRR Kaiwen Zuo, Yirui Jiang, Fan Mo, Pietro Lio
2024	—	`conf`	Language Model Knowledge Distillation for Efficient Question Answering in Spanish. Tiny Papers @ ICLR Adrián Bazaga, Pietro Lio, Gos Micklem
2024	J	`jnl`	Masked Attention is All You Need for Graphs. CoRR David Buterez, Jon Paul Janet, Dino Oglic, Pietro Lio
2024	—	`conf`	Metric Learning for Clifford Group Equivariant Neural Networks. GRaM Riccardo Ali, Paulina Kulyte, Haitz Sáez de Ocáriz Borde, Pietro Lio
2024	A*	`conf`	Position: Topological Deep Learning is the New Frontier for Relational Learning. ICML Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
2024	J	`jnl`	Predicting time-varying flux and balance in metabolic systems using structured neural-ODE processes. CoRR Santanu Rathod, Pietro Lio, Xiao Zhang
2024	J	`jnl`	SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN network. Expert Syst. Appl. Xiaofeng Lu, Jinglun Zhao, Senhao Zhu, Pietro Lio
2024	J	`jnl`	Solving the enigma: Deriving optimal explanations of deep networks. CoRR Michail Mamalakis, Antonios Mamalakis, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Graham K. Murray, John Suckling, Pietro Lio
2024	J	`jnl`	Structure-based drug design with equivariant diffusion models. Nat. Comput. Sci. Arne 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
2024	J	`jnl`	The Explanation Necessity for Healthcare AI. CoRR Michail Mamalakis, Héloïse de Vareilles, Graham K. Murray, Pietro Lio, John Suckling
2024	A*	`conf`	Unsupervised Pretraining for Fact Verification by Language Model Distillation. ICLR Adrián Bazaga, Pietro Lio, Gos Micklem
2024	J	`jnl`	ZeroPur: Succinct Training-Free Adversarial Purification. CoRR Xiuli Bi, Zonglin Yang, Bo Liu, Xiaodong Cun, Chi-Man Pun, Pietro Lio, Bin Xiao
2024	—	`conf`	xAI-Drop: Don't Use What You Cannot Explain. LoG Vincenzo Marco De Luca, Antonio Longa, Pietro Lio, Andrea Passerini
2023	J	`jnl`	A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition. CoRR Michail Mamalakis, Héloïse de Vareilles, Atheer AI-Manea, Samantha C. Mitchell, Ingrid Agartz, Lynn Egeland Morch-Johnsen, Jane R. Garrison, Jon S. Simons, Pietro Lio, John Suckling, Graham K. Murray
2023	J	`jnl`	A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
2023	B	`conf`	A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation Learning. IEEE Big Data Zhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio
2023	J	`jnl`	A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. CoRR Kieran Didi, Francisco Vargas, Simon V. Mathis, Vincent Dutordoir, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio
2023	—	`conf`	Adaptive Distance Message Passing From the Multi-Relational Edge View. Tiny Papers @ ICLR Zhongtian Sun, Alexandra I. Cristea, Pietro Lio, Jialin Yu
2023	—	`conf`	Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. TAG-ML Oguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini
2023	—	`conf`	DBGDGM: Dynamic Brain Graph Deep Generative Model. MIDL Alexander Campbell, Simeon Emilov Spasov, Nicola Toschi, Pietro Lio
2023	—	`conf`	DBGSL: Dynamic Brain Graph Structure Learning. MIDL Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio
2023	J	`jnl`	Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation. CoRR Jialin Chen, Yuelin Wang, Cristian Bodnar, Rex Ying, Pietro Lio, Yuguang Wang
2023	J	`jnl`	Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities. Trans. Mach. Learn. Res. Antonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Lio, Franco Scarselli, Andrea Passerini
2023	J	`jnl`	Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design. CoRR Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernárdez, Olga Zaghen, Simone Scardapane, Pietro Lio
2023	J	`jnl`	Incorporating LLM Priors into Tabular Learners. CoRR Max Zhu, Sinisa Stanivuk, Andrija Petrovic, Mladen Nikolic, Pietro Lio
2023	J	`jnl`	Interpretable Graph Networks Formulate Universal Algebra Conjectures. CoRR Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lio, Pietro Barbiero
2023	A*	`conf`	Interpretable Neural-Symbolic Concept Reasoning. ICML Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
2023	—	`ch.`	Learning Logic Explanations by Neural Networks. Compendium of Neurosymbolic Artificial Intelligence Gabriele Ciravegna, Francesco Giannini, Pietro Barbiero, Marco Gori, Pietro Lio, Marco Maggini, Stefano Melacci
2023	J	`jnl`	MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model. AI Open Zhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio
2023	—	`conf`	Neural Algorithmic Reasoning for Combinatorial Optimisation. LoG Dobrik Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio
2023	A*	`conf`	On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein
2023	A*	`conf`	On the Expressive Power of Geometric Graph Neural Networks. ICML Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio
2023	J	`jnl`	RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine Learning. IEEE Trans. Parallel Distributed Syst. Xiaofeng Lu, Chao Liu, Senhao Zhu, Yilu Mao, Pietro Lio, Pan Hui
2023	J	`jnl`	StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI images. J. King Saud Univ. Comput. Inf. Sci. Anjir Ahmed Chowdhury, S. M. Hasan Mahmud, Khadija Kubra Shahjalal Hoque, Kawsar Ahmed, Francis M. Bui, Pietro Lio, Mohammad Ali Moni, Fahad Ahmed Al-Zahrani
2023	—	`conf`	Will More Expressive Graph Neural Networks Do Better on Generative Tasks? LoG Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao