Pietro Lio

Publication Activity (10 Years)

Years Active: 2023-2024
Publications (10 Years): 34

Top Topics

Hypergraph Model

Top Venues

Publications

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 (2024)
Adrián Bazaga, Pietro Lio, Gos Micklem
Language Model Knowledge Distillation for Efficient Question Answering in Spanish. Tiny Papers @ ICLR (2024)
Panfeng Cao, Pietro Lio
GenRec: Generative Personalized Sequential Recommendation. CoRR (2024)
Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik
Dynamics-Informed Protein Design with Structure Conditioning. ICLR (2024)
Michail Mamalakis, Héloïse de Vareilles, Graham K. Murray, Pietro Lio, John Suckling
The Explanation Necessity for Healthcare AI. CoRR (2024)
Xiuli Bi, Zonglin Yang, Bo Liu, Xiaodong Cun, Chi-Man Pun, Pietro Lio, Bin Xiao
ZeroPur: Succinct Training-Free Adversarial Purification. CoRR (2024)
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 (2024)
Adrián Bazaga, Pietro Lio, Gos Micklem
Unsupervised Pretraining for Fact Verification by Language Model Distillation. ICLR (2024)
David Buterez, Jon Paul Janet, Dino Oglic, Pietro Lio
Masked Attention is All You Need for Graphs. CoRR (2024)
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 (2024)
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 (2024)
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)
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 (2024)
Dobrik Georgiev, Danilo Numeroso, Davide Bacciu, Pietro Lio
Neural Algorithmic Reasoning for Combinatorial Optimisation. LoG (2023)
Alexander Campbell, Simeon Emilov Spasov, Nicola Toschi, Pietro Lio
DBGDGM: Dynamic Brain Graph Deep Generative Model. MIDL (2023)
Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio
DBGSL: Dynamic Brain Graph Structure Learning. MIDL (2023)
Kieran Didi, Francisco Vargas, Simon V. Mathis, Vincent Dutordoir, Emile Mathieu, Urszula J. Komorowska, Pietro Lio
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. CoRR (2023)
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) (2023)
Michail Mamalakis, Héloïse de Vareilles, Atheer AI-Manea, Samantha C. Mitchell, Ingrid Arartz, Lynn Egeland Morch-Johnsen, Jane R. Garrison, Jon S. Simons, Pietro Lio, John Suckling, Graham K. Murray
A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition. CoRR (2023)
Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernárdez, Olga Zaghen, Simone Scardapane, Pietro Lio
Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design. CoRR (2023)
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) (2023)
Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lio, Pietro Barbiero
Interpretable Graph Networks Formulate Universal Algebra Conjectures. CoRR (2023)
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)
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)
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)
Jialin Chen, Yuelin Wang, Cristian Bodnar, Rex Ying, Pietro Lio, Yuguang Wang
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation. CoRR (2023)
Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR (2023)
Max Zhu, Sinisa Stanivuk, Andrija Petrovic, Mladen Nikolic, Pietro Lio
Incorporating LLM Priors into Tabular Learners. CoRR (2023)
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)
Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao
Will More Expressive Graph Neural Networks Do Better on Generative Tasks? LoG (2023)
Zhongtian Sun, Alexandra I. Cristea, Pietro Lio, Jialin Yu
Adaptive Distance Message Passing From the Multi-Relational Edge View. Tiny Papers @ ICLR (2023)
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 (2023)
Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Lio
On the Expressive Power of Geometric Graph Neural Networks. ICML (2023)
Zhongtian Sun, Anoushka Harit, Alexandra I. Cristea, Jingyun Wang, Pietro Lio
A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation Learning. BigData (2023)