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ORCIDPietro Liò
Pietro Lió – Pietro Lio' – Pietro Lio
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- affiliation: University of Cambridge, Department of Computer Science and Technology, UK
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2020 – today
- 2025
[j146]Zhenyu Yang
, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò:
State of the Art and Potentialities of Graph-level Learning. ACM Comput. Surv. 57(2): 28:1-28:40 (2025)- [j145]Caihong Yan, Xiaofeng Lu, Pietro Lio, Pan Hui, Daojing He:
Self-Simulation and Meta-Model Aggregation-Based Heterogeneous-Graph-Coupled Federated Learning. IEEE Internet Things J. 12(1): 198-212 (2025) - [j144]Francesco Prinzi, Pietro Barbiero, Claudia Greco, Terry Amorese, Gennaro Cordasco, Pietro Liò, Salvatore Vitabile, Anna Esposito:
Using AI explainable models and handwriting/drawing tasks for psychological well-being. Inf. Syst. 127: 102465 (2025) - 2024
- [j143]Roksana Akter Raisa, Ayesha Siddika Rodela, Mohammad Abu Yousuf, A. K. M. Azad, Salem A. Alyami, Pietro Liò, Md Zahidul Islam, Ganna Pogrebna, Mohammad Ali Moni:
Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study. IEEE Access 12: 122959-122987 (2024) - [j142]Xiaofeng Lu, Jinglun Zhao, Senhao Zhu, Pietro Lio:
SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN network. Expert Syst. Appl. 250: 123922 (2024) - [j141]Nasirul Mumenin, Mohammad Abu Yousuf, Md Asif Nashiry, A. K. M. Azad, Salem A. Alyami, Pietro Lio', Mohammad Ali Moni:
ASDNet: A robust involution-based architecture for diagnosis of autism spectrum disorder utilising eye-tracking technology. IET Comput. Vis. 18(5): 666-681 (2024) - [j140]Francesco Bardozzo, Andrea Terlizzi, Claudio Simoncini, Pietro Lió, Roberto Tagliaferri:
Elegans-AI: How the connectome of a living organism could model artificial neural networks. Neurocomputing 584: 127598 (2024) - [j139]Lintao Yang, Pietro Liò, Xu Shen, Yuyang Zhang, Chengbin Peng:
Adaptive multi-scale Graph Neural Architecture Search framework. Neurocomputing 599: 128094 (2024) - [j138]Zhikang Wang, Jiani Ma, Qian Gao, Chris Bain, Seiya Imoto, Pietro Liò, Hongmin Cai, Hao Chen, Jiangning Song:
Dual-stream multi-dependency graph neural network enables precise cancer survival analysis. Medical Image Anal. 97: 103252 (2024) - [j137]Yuanqi Du, Arian R. Jamasb, Jeff Guo, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, Tom L. Blundell:
Machine learning-aided generative molecular design. Nat. Mac. Intell. 6(6): 589-604 (2024) - [j136]Till Siebenmorgen, Filipe Menezes, Sabrina Benassou, Erinc Merdivan, Kieran Didi, André Santos Dias Mourão, Radoslaw Kitel, Pietro Liò, Stefan Kesselheim, Marie Piraud, Fabian J. Theis, Michael Sattler, Grzegorz M. Popowicz:
MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery. Nat. Comput. Sci. 4(5): 367-378 (2024) - [j135]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:
Structure-based drug design with equivariant diffusion models. Nat. Comput. Sci. 4(12): 899-909 (2024) - [j134]Alauddin Sabari, Imran Hasan, Salem A. Alyami, Pietro Liò, Md. Sadek Ali, Mohammad Ali Moni, A. K. M. Azad:
LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond. Softw. Impacts 22: 100718 (2024) - [j133]Xu Shen, Pietro Liò, Lintao Yang, Ru Yuan, Yuyang Zhang, Chengbin Peng:
Graph Rewiring and Preprocessing for Graph Neural Networks Based on Effective Resistance. IEEE Trans. Knowl. Data Eng. 36(11): 6330-6343 (2024) - [j132]Ming Li, Alessio Micheli, Yu Guang Wang, Shirui Pan, Pietro Lió, Giorgio Stefano Gnecco, Marcello Sanguineti:
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4367-4372 (2024) - [c197]Xiangyu Zhao, Zehui Li, Mingzhu Shen, Guy-Bart Stan, Pietro Liò, Yiren Zhao:
Enhancing Node Representations for Real-World Complex Networks with Topological Augmentation. ECAI 2024: 1487-1494 - [c196]Adrián Bazaga, Pietro Lio, Gos Micklem:
HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs. EMNLP (Findings) 2024: 9181-9193 - [c195]Adrián Bazaga, Pietro Lio, Gos Micklem:
Language Model Knowledge Distillation for Efficient Question Answering in Spanish. Tiny Papers @ ICLR 2024 - [c194]Adrián Bazaga, Pietro Lio, Gos Micklem:
Unsupervised Pretraining for Fact Verification by Language Model Distillation. ICLR 2024 - [c193]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:
Evaluating Representation Learning on the Protein Structure Universe. ICLR 2024 - [c192]Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik:
Dynamics-Informed Protein Design with Structure Conditioning. ICLR 2024 - [c191]Keke Huang, Yu Guang Wang, Ming Li, Pietro Lio:
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing. ICML 2024 - [c190]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:
Position: Topological Deep Learning is the New Frontier for Relational Learning. ICML 2024 - [c189]Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò:
Integrating Structure and Sequence: Protein Graph Embeddings via GNNs and LLMs. ICPRAM 2024: 582-593 - [c188]Francesco Ceccarelli, Francesco Prinzi, Pietro Liò, Salvatore Vitabile, Sean B. Holden:
MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI. IJCNN 2024: 1-8 - [c187]Lorenzo Giusti, Teodora Reu, Francesco Ceccarelli, Cristian Bodnar, Pietro Liò:
Topological Message Passing for Higher - Order and Long - Range Interactions. IJCNN 2024: 1-8 - [c186]Lihao Liu, Yanqi Cheng, Zhongying Deng, Shujun Wang, Dongdong Chen, Xiaowei Hu, Pietro Liò, Carola-Bibiane Schönlieb, Angelica E. Avilés-Rivero:
TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. ACM Multimedia 2024: 1265-1273 - [c185]Keke Huang, Wencai Cao, Hoang Ta, Xiaokui Xiao, Pietro Liò:
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach. WWW 2024: 1057-1068 - [c184]Francesco Giannini, Stefano Fioravanti, Pietro Barbiero, Alberto Tonda, Pietro Liò, Elena Di Lavore:
Categorical Foundation of Explainable AI: A Unifying Theory. xAI (3) 2024: 185-206 - [i251]Dobrik Georgiev, Pietro Liò, Davide Buffelli:
The Deep Equilibrium Algorithmic Reasoner. CoRR abs/2402.06445 (2024) - [i250]Adrián Bazaga, Pietro Liò, Gos Micklem:
HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs. CoRR abs/2402.07309 (2024) - [i249]Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, 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:
Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR abs/2402.08871 (2024) - [i248]David Buterez, Jon Paul Janet, Dino Oglic, Pietro Lio:
Masked Attention is All You Need for Graphs. CoRR abs/2402.10793 (2024) - [i247]Xiangyu Zhao, Zehui Li, Mingzhu Shen, Guy-Bart Stan, Pietro Liò, Yiren Zhao:
Enhancing Real-World Complex Network Representations with Hyperedge Augmentation. CoRR abs/2402.13033 (2024) - [i246]Elsa Lawrence, Adham El-Shazly, Srijit Seal, Chaitanya K. Joshi, Pietro Liò, Shantanu Singh, Andreas Bender, Pietro Sormanni, Matthew Greenig:
Understanding Biology in the Age of Artificial Intelligence. CoRR abs/2403.04106 (2024) - [i245]Annamaria Defilippo, Pierangelo Veltri, Pietro Lió, Pietro Hiram Guzzi:
Leveraging graph neural networks for supporting Automatic Triage of Patients. CoRR abs/2403.07038 (2024) - [i244]Keke Huang, Wencai Cao, Hoang Ta, Xiaokui Xiao, Pietro Liò:
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach. CoRR abs/2403.07954 (2024) - [i243]Samitha Somathilaka, Adrian Ratwatte, Sasitharan Balasubramaniam, Mehmet Can Vuran, Witawas Srisa-an, Pietro Liò:
Wet TinyML: Chemical Neural Network Using Gene Regulation and Cell Plasticity. CoRR abs/2403.08549 (2024) - [i242]Tiansi Dong, Mateja Jamnik, Pietro Liò:
Sphere Neural-Networks for Rational Reasoning. CoRR abs/2403.15297 (2024) - [i241]Ugo Lomoio, Pierangelo Veltri, Pietro Hiram Guzzi, Pietro Lio':
DCAE-SR: Design of a Denoising Convolutional Autoencoder for reconstructing Electrocardiograms signals at Super Resolution. CoRR abs/2404.15307 (2024) - [i240]Miruna T. Cretu, Charles Harris, Julien Roy, Emmanuel Bengio, Pietro Liò:
SynFlowNet: Towards Molecule Design with Guaranteed Synthesis Pathways. CoRR abs/2405.01155 (2024) - [i239]Andrea Barucci, Giulia Ciacci, Pietro Liò, Tiago Azevedo, Andrea Di Cencio, Marco Merella, Giovanni Bianucci, Giulia Bosio, Simone Casati, Alberto Collareta:
Artificial Intelligence-powered fossil shark tooth identification: Unleashing the potential of Convolutional Neural Networks. CoRR abs/2405.04189 (2024) - [i238]Michail Mamalakis, Antonios Mamalakis, Ingrid Agartz, Lynn Egeland Mørch-Johnsen, Graham K. Murray, John Suckling, Pietro Lio:
Solving the enigma: Deriving optimal explanations of deep networks. CoRR abs/2405.10008 (2024) - [i237]Keke Huang, Yu Guang Wang, Ming Li, Pietro Liò:
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing. CoRR abs/2405.12474 (2024) - [i236]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:
Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification. CoRR abs/2405.19204 (2024) - [i235]Bao Nguyen, Lorenzo Sani, Xinchi Qiu, Pietro Liò, Nicholas D. Lane:
Sheaf HyperNetworks for Personalized Federated Learning. CoRR abs/2405.20882 (2024) - [i234]Michail Mamalakis, Héloïse de Vareilles, Graham K. Murray, Pietro Lio, John Suckling:
The Explanation Necessity for Healthcare AI. CoRR abs/2406.00216 (2024) - [i233]Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio:
DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. CoRR abs/2406.01781 (2024) - [i232]Andrei Margeloiu, Adrián Bazaga, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting. CoRR abs/2406.01805 (2024) - [i231]Xiuli Bi, Zonglin Yang, Bo Liu, Xiaodong Cun, Chi-Man Pun, Pietro Lio, Bin Xiao:
ZeroPur: Succinct Training-Free Adversarial Purification. CoRR abs/2406.03143 (2024) - [i230]Veljko Kovac, Erik J. Bekkers, Pietro Liò, Floor Eijkelboom:
E(n) Equivariant Message Passing Cellular Networks. CoRR abs/2406.03145 (2024) - [i229]Max Zhu, Adrián Bazaga, Pietro Liò:
FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models. CoRR abs/2406.04501 (2024) - [i228]Paulina Kulyte, Francisco Vargas, Simon Valentin Mathis, Yu Guang Wang, José Miguel Hernández-Lobato, Pietro Liò:
Improving Antibody Design with Force-Guided Sampling in Diffusion Models. CoRR abs/2406.05832 (2024) - [i227]Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian R. Jamasb, Charles Harris, Simon V. Mathis, Kieran Didi, Bryan Hooi, Pietro Liò:
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. CoRR abs/2406.13839 (2024) - [i226]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:
Evaluating representation learning on the protein structure universe. CoRR abs/2406.13864 (2024) - [i225]Elisa Gómez de Lope, Saurabh Deshpande, Ramón Viñas Torné, Pietro Liò, Enrico Glaab, Stéphane P. A. Bordas:
Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease. CoRR abs/2406.14442 (2024) - [i224]James Rowbottom, Georg Maierhofer, Teo Deveney, Katharina Schratz, Pietro Liò, Carola-Bibiane Schönlieb, Chris J. Budd:
G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. CoRR abs/2407.04516 (2024) - [i223]Riccardo Ali, Paulina Kulyte, Haitz Sáez de Ocáriz Borde, Pietro Liò:
Metric Learning for Clifford Group Equivariant Neural Networks. CoRR abs/2407.09926 (2024) - [i222]Vincenzo Marco De Luca, Antonio Longa, Andrea Passerini, Pietro Liò:
xAI-Drop: Don't Use What You Cannot Explain. CoRR abs/2407.20067 (2024) - [i221]Ferran Hernandez Caralt, Guillermo Bernárdez Gil, Iulia Duta, Pietro Liò, Eduard Alarcón-Cot:
Joint Diffusion Processes as an Inductive Bias in Sheaf Neural Networks. CoRR abs/2407.20597 (2024) - [i220]Panfeng Cao, Pietro Lio:
GenRec: Generative Personalized Sequential Recommendation. CoRR abs/2407.21191 (2024) - [i219]Yiqing Shen, Zan Chen, Michail Mamalakis, Yungeng Liu, Tianbin Li, Yanzhou Su, Junjun He, Pietro Liò, Yu Guang Wang:
TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering. CoRR abs/2408.15299 (2024) - [i218]Richard Bergna, Sergio Calvo-Ordoñez, Felix L. Opolka, Pietro Liò, José Miguel Hernández-Lobato:
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. CoRR abs/2408.16115 (2024) - [i217]Chong Wang, Mengyao Li, Junjun He, Zhongruo Wang, Erfan Darzi, Zan Chen, Jin Ye, Tianbin Li, Yanzhou Su, Jing Ke, Kaili Qu, Shuxin Li, Yi Yu, Pietro Liò, Tianyun Wang, Yu Guang Wang, Yiqing Shen:
A Survey for Large Language Models in Biomedicine. CoRR abs/2409.00133 (2024) - [i216]Zeno Kujawa, John Poole, Dobrik Georgiev, Danilo Numeroso, Pietro Liò:
Neural Algorithmic Reasoning with Multiple Correct Solutions. CoRR abs/2409.06953 (2024) - [i215]Luke Braithwaite, Iulia Duta, Pietro Liò:
Heterogeneous Sheaf Neural Networks. CoRR abs/2409.08036 (2024) - [i214]Vikash Singh, Matthew Khanzadeh, Vincent Davis, Harrison Rush, Emanuele Rossi, Jesse Shrader, Pietro Lio:
Bayesian Binary Search. CoRR abs/2410.01771 (2024) - [i213]Iulia Duta, Pietro Liò:
SPHINX: Structural Prediction using Hypergraph Inference Network. CoRR abs/2410.03208 (2024) - [i212]Shiye Su, Iulia Duta, Lucie Charlotte Magister, Pietro Liò:
Explaining Hypergraph Neural Networks: From Local Explanations to Global Concepts. CoRR abs/2410.07764 (2024) - [i211]Santanu Rathod, Pietro Lio, Xiao Zhang:
Predicting time-varying flux and balance in metabolic systems using structured neural-ODE processes. CoRR abs/2410.14426 (2024) - [i210]Dobrik Georgiev, JJ Wilson, Davide Buffelli, Pietro Liò:
Deep Equilibrium Algorithmic Reasoning. CoRR abs/2410.15059 (2024) - [i209]Jihan K. Zaki, Jakub Tomasik, Jade A. McCune, Sabine Bahn, Pietro Liò, Oren A. Scherman:
Explainable Deep Learning Framework for SERS Bio-quantification. CoRR abs/2411.08082 (2024) - 2023
- [j131]Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. Artif. Intell. 314: 103822 (2023) - [j130]Zhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio:
MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model. AI Open 4: 165-174 (2023) - [j129]Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, Md. Mehedi Hasan, Mohammad Ali Moni, Pietro Lio', Watshara Shoombuatong:
PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. Comput. Biol. Medicine 152: 106368 (2023) - [j128]Zhikang Wang, Qian Gao, Xiaoping Yi, Xinyu Zhang, Yiwen Zhang, Daokun Zhang, Pietro Liò, Chris Bain, Richard Bassed, Shanshan Li, Yuming Guo, Seiya Imoto, Jianhua Yao, Roger J. Daly, Jiangning Song:
Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images. Comput. Methods Programs Biomed. 241: 107733 (2023) - [j127]Andrija Petrovic, Mladen Nikolic, Ugljesa Bugaric, Boris Delibasic, Pietro Liò:
Controlling highway toll stations using deep learning, queuing theory, and differential evolution. Eng. Appl. Artif. Intell. 119: 105683 (2023) - [j126]David Buterez, Jon Paul Janet, Steven J. Kiddle, Pietro Liò:
MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. J. Chem. Inf. Model. 63(9): 2667-2678 (2023) - [j125]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:
StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI images. J. King Saud Univ. Comput. Inf. Sci. 35(8): 101647 (2023) - [j124]Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb:
Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. 5(7): 681-686 (2023) - [j123]Ramón Viñas, Chaitanya K. Joshi, Dobrik Georgiev, Phillip Lin, Bianca Dumitrascu, Eric R. Gamazon, Pietro Liò:
Hypergraph factorization for multi-tissue gene expression imputation. Nat. Mac. Intell. 5(7): 739-753 (2023) - [j122]Md. Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Lio', Julian M. W. Quinn, Mohammad Ali Moni:
HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. Neural Networks 162: 271-287 (2023) - [j121]Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolò Pancino, Pietro Lió:
Modular Multi-Source Prediction of Drug Side-Effects With DruGNN. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 1211-1220 (2023) - [j120]Junwei Yang, Xiao-Xin Li, Feihong Liu, Dong Nie, Pietro Liò, Haikun Qi, Dinggang Shen:
Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast. IEEE Trans. Medical Imaging 42(5): 1363-1373 (2023) - [j119]Antonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Lio, Franco Scarselli, Andrea Passerini:
Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities. Trans. Mach. Learn. Res. 2023 (2023) - [j118]Xiaofeng Lu, Fan Yang, Luwen Zou, Pietro Liò, Pan Hui:
An LTE Authentication and Key Agreement Protocol Based on the ECC Self-Certified Public Key. IEEE/ACM Trans. Netw. 31(3): 1101-1116 (2023) - [j117]Xiaofeng Lu, Chao Liu, Senhao Zhu, Yilu Mao, Pietro Lio, Pan Hui:
RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine Learning. IEEE Trans. Parallel Distributed Syst. 34(12): 3266-3279 (2023) - [c183]Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. AAAI 2023: 9081-9089 - [c182]Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Liò:
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis. AAAI 2023: 10675-10683 - [c181]Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liò, Mihaela van der Schaar:
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. AISTATS 2023: 10279-10304 - [c180]Zhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio:
A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation Learning. IEEE Big Data 2023: 5930-5939 - [c179]Xiuli Bi, Shizhan Tang, Zonglin Yang, Xin Deng, Bin Xiao, Pietro Liò:
MMCTNet: Multi-Modal Cony-Transformer Network for Predicting Good and Poor Outcomes in Cardiac Arrest Patients. CinC 2023: 1-4 - [c178]Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
SCOTCH and SODA: A Transformer Video Shadow Detection Framework. CVPR 2023: 10449-10458 - [c177]Guillermo Bernárdez, Lev Telyatnikov, Eduard Alarcón, Albert Cabellos-Aparicio, Pere Barlet-Ros, Pietro Liò:
Topological Network Traffic Compression. GNNet@CoNEXT 2023: 7-12 - [c176]Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Liò, Andrea Passerini:
Global Explainability of GNNs via Logic Combination of Learned Concepts. ICLR 2023 - [c175]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. ICLR 2023 - [c174]Zhongtian Sun, Alexandra I. Cristea, Pietro Lio, Jialin Yu:
Adaptive Distance Message Passing From the Multi-Relational Edge View. Tiny Papers @ ICLR 2023 - [c173]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. ICML 2023: 1801-1825 - [c172]Francesco Di Giovanni, Lorenzo Giusti, Federico Barbero, Giulia Luise, Pietro Lio, Michael M. Bronstein:
On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. ICML 2023: 7865-7885 - [c171]Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio:
On the Expressive Power of Geometric Graph Neural Networks. ICML 2023: 15330-15355 - [c170]Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao:
Will More Expressive Graph Neural Networks Do Better on Generative Tasks? LoG 2023: 21 - [c169]Dobrik Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio:
Neural Algorithmic Reasoning for Combinatorial Optimisation. LoG 2023: 28 - [c168]Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio:
DBGSL: Dynamic Brain Graph Structure Learning. MIDL 2023: 1318-1345 - [c167]Alexander Campbell, Simeon Emilov Spasov, Nicola Toschi, Pietro Lio:
DBGDGM: Dynamic Brain Graph Deep Generative Model. MIDL 2023: 1346-1371 - [c166]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Liò, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. NeSy 2023: 422-423 - [c165]Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. NeSy 2023: 432-433 - [c164]Iulia Duta, Giulia Cassarà, Fabrizio Silvestri, Pietro Lió:
Sheaf Hypergraph Networks. NeurIPS 2023 - [c163]Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lió, Pietro Barbiero:
Interpretable Graph Networks Formulate Universal Algebra Conjectures. NeurIPS 2023 - [c162]Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. NeurIPS 2023 - [c161]Oguzhan Keskin, Alisia Maria Lupidi, Stefano Fioravanti, Lucie Charlotte Magister, Pietro Barbiero, Pietro Lio, Francesco Giannini:
Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. TAG-ML 2023: 156-168 - [c160]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Graph classification Gaussian processes via spectral features. UAI 2023: 1575-1585 - [c159]