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ORCIDPietro Liò
Pietro Lió – Pietro Lio'
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- affiliation: University of Cambridge, Department of Computer Science and Technology, UK
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2020 – today
- 2023
[j119]Gabriele Ciravegna
, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. Artif. Intell. 314: 103822 (2023)- [j118]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) - [j117]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) - [i158]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Liò:
A Comprehensive Survey of Graph-level Learning. CoRR abs/2301.05860 (2023) - [i157]Chaitanya K. Joshi, Cristian Bodnar, Simon V. Mathis, Taco Cohen, Pietro Liò:
On the Expressive Power of Geometric Graph Neural Networks. CoRR abs/2301.09308 (2023) - [i156]Alexander Campbell, Simeon E. Spasov, Nicola Toschi, Pietro Liò:
DBGDGM: Dynamic Brain Graph Deep Generative Model. CoRR abs/2301.11408 (2023) - [i155]Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao:
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR abs/2301.11517 (2023) - [i154]Antonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Liò, Franco Scarselli, Andrea Passerini:
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities. CoRR abs/2302.01018 (2023) - [i153]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. CoRR abs/2302.02941 (2023) - [i152]Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Liò:
GCI: A (G)raph (C)oncept (I)nterpretation Framework. CoRR abs/2302.04899 (2023) - [i151]Filip Svoboda, Gianluca Mittone, Nicholas D. Lane, Pietro Liò:
A Federated Learning Benchmark for Drug-Target Interaction. CoRR abs/2302.07684 (2023) - [i150]Jin Zhu, Guang Yang, Pietro Liò:
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuning. CoRR abs/2302.11184 (2023) - [i149]Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liò, Mihaela van der Schaar:
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. CoRR abs/2302.12749 (2023) - [i148]Md. Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin, Pietro Liò, 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. CoRR abs/2303.06020 (2023) - 2022
- [j116]Ramón Viñas, Helena Andrés-Terré, Pietro Liò, Kevin Bryson:
Adversarial generation of gene expression data. Bioinform. 38(3): 730-737 (2022) - [j115]David Buterez, Ioana Bica, Ifrah Tariq, Helena Andrés-Terré, Pietro Liò:
CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinform. 38(5): 1277-1286 (2022) - [j114]Paul Scherer, Maja Trebacz, Nikola Simidjievski, Ramón Viñas, Zohreh Shams, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò:
Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. Bioinform. 38(5): 1320-1327 (2022) - [j113]Phasit Charoenkwan, Nalini Schaduangrat, Mohammad Ali Moni, Pietro Lio', Balachandran Manavalan, Watshara Shoombuatong:
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Comput. Biol. Medicine 146: 105704 (2022) - [j112]Phasit Charoenkwan, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Balachandran Manavalan, Watshara Shoombuatong:
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Comput. Biol. Medicine 148: 105700 (2022) - [j111]Helena Coggan, Helena Andrés-Terré, Pietro Liò:
A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth. Frontiers Big Data 5 (2022) - [j110]Giovanna Maria Dimitri, Simeon E. Spasov, Andrea Duggento, Luca Passamonti, Pietro Lió, Nicola Toschi:
Multimodal and multicontrast image fusion via deep generative models. Inf. Fusion 88: 146-160 (2022) - [j109]Xiaofeng Lu, Yuying Liao, Chao Liu, Pietro Liò, Pan Hui:
Heterogeneous Model Fusion Federated Learning Mechanism Based on Model Mapping. IEEE Internet Things J. 9(8): 6058-6068 (2022) - [j108]Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, Pietro Lio', Mohammad Ali Moni, Watshara Shoombuatong:
Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. J. Comput. Aided Mol. Des. 36(11): 781-796 (2022) - [j107]Tiago Azevedo, Alexander Campbell, Rafael Romero-Garcia, Luca Passamonti, Richard A. I. Bethlehem, Pietro Liò, Nicola Toschi:
A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data. Medical Image Anal. 79: 102471 (2022) - [j106]Stefanos Zafeiriou, Michael M. Bronstein, Taco Cohen, Oriol Vinyals, Le Song, Jure Leskovec, Pietro Liò, Joan Bruna, Marco Gori:
Guest Editorial: Non-Euclidean Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 723-726 (2022) - [j105]Yutong Chen, Carola-Bibiane Schönlieb, Pietro Liò, Tim Leiner, Pier Luigi Dragotti, Ge Wang, Daniel Rueckert, David N. Firmin, Guang Yang:
AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. Proc. IEEE 110(2): 224-245 (2022) - [j104]Animesh Chaturvedi, Aruna Tiwari, Shubhangi Chaturvedi, Pietro Liò:
System Neural Network: Evolution and Change Based Structure Learning. IEEE Trans. Artif. Intell. 3(3): 426-435 (2022) - [c148]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci:
Entropy-Based Logic Explanations of Neural Networks. AAAI 2022: 6046-6054 - [c147]Dobrik Georgiev, Pietro Barbiero, Dmitry Kazhdan, Petar Velickovic, Pietro Lió:
Algorithmic Concept-Based Explainable Reasoning. AAAI 2022: 6685-6693 - [c146]Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong:
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. AISTATS 2022: 4818-4834 - [c145]Felix L. Opolka, Pietro Liò:
Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes. AISTATS 2022: 4835-4852 - [c144]Xiaofeng Lu, Renyu Pang, Pietro Liò:
Poster: CFMAP: A Robust CPU Clock Fingerprint Model for Device Authentication. CCS 2022: 3407-3409 - [c143]Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò:
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CIKM Workshops 2022 - [c142]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. EMNLP 2022: 8838-8857 - [c141]Alexander Campbell, Lorena Qendro, Pietro Liò, Cecilia Mascolo:
Robust and Efficient Uncertainty Aware Biosignal Classification via Early Exit Ensembles. ICASSP 2022: 3998-4002 - [c140]Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane:
Do We Need Anisotropic Graph Neural Networks? ICLR 2022 - [c139]Junchao Fan, Jiawei Pei, Xiuli Bi, Bin Xiao, Pietro Liò:
Context Correlation Aware Network for Cardiac Segmentation. ICME 2022: 1-6 - [c138]Ben J. Day, Ramón Viñas Torné, Nikola Simidjievski, Pietro Lió:
Attentional Meta-learners for Few-shot Polythetic Classification. ICML 2022: 4867-4889 - [c137]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió:
3D Infomax improves GNNs for Molecular Property Prediction. ICML 2022: 20479-20502 - [c136]Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Zhitao Ying, Jure Leskovec, Pietro Liò:
Learning Graph Search Heuristics. LoG 2022: 10 - [c135]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yu Guang Wang:
Well-Conditioned Spectral Transforms for Dynamic Graph Representation. LoG 2022: 12 - [c134]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed Representations of Graphs for Drug Pair Scoring. LoG 2022: 22 - [c133]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. LoG 2022: 54 - [c132]Pengfang Qian, Junwei Yang, Pietro Lió, Peng Hu, Haikun Qi:
Joint Group-Wise Motion Estimation and Segmentation of Cardiac Cine MR Images Using Recurrent U-Net. MIUA 2022: 65-74 - [c131]Xiaofeng Lu, Jinglun Zhao, Pietro Lió:
Robust android malware detection based on subgraph network and denoising GCN network. MobiSys 2022: 549-550 - [c130]Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration. WBIR 2022: 190-193 - [i147]Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein:
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. CoRR abs/2202.04579 (2022) - [i146]Pietro Bongini, Franco Scarselli, Monica Bianchini, Giovanna Maria Dimitri, Niccolò Pancino, Pietro Liò:
Modular multi-source prediction of drug side-effects with DruGNN. CoRR abs/2202.08147 (2022) - [i145]Charles N. Christensen, Meng Lu, Edward N. Ward, Pietro Liò, Clemens F. Kaminski:
Spatio-temporal Vision Transformer for Super-resolution Microscopy. CoRR abs/2203.00030 (2022) - [i144]Lihao Liu, Zhening Huang, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I. Avilés-Rivero:
PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation. CoRR abs/2203.05684 (2022) - [i143]Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Liò, Daniel Rueckert, Yonina C. Eldar, Guang Yang:
Data and Physics Driven Learning Models for Fast MRI - Fundamentals and Methodologies from CNN, GAN to Attention and Transformers. CoRR abs/2204.01706 (2022) - [i142]Christopher Wei Jin Goh, Cristian Bodnar, Pietro Liò:
Simplicial Attention Networks. CoRR abs/2204.09455 (2022) - [i141]Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb:
Classification of datasets with imputed missing values: does imputation quality matter? CoRR abs/2206.08478 (2022) - [i140]Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò:
Sheaf Neural Networks with Connection Laplacians. CoRR abs/2206.08702 (2022) - [i139]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
Approximate Equivariance SO(3) Needlet Convolution. CoRR abs/2206.10385 (2022) - [i138]Davide Buffelli, Pietro Liò, Fabio Vandin:
SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. CoRR abs/2207.07888 (2022) - [i137]Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Pietro Liò, Mateja Jamnik:
Encoding Concepts in Graph Neural Networks. CoRR abs/2207.13586 (2022) - [i136]Han Xuanyuan, Pietro Barbiero, Dobrik Georgiev, Lucie Charlotte Magister, Pietro Lió:
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis. CoRR abs/2208.10609 (2022) - [i135]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Liò, Mateja Jamnik:
Concept Embedding Models. CoRR abs/2209.09056 (2022) - [i134]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed representations of graphs for drug pair scoring. CoRR abs/2209.09383 (2022) - [i133]Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Liò:
DBGSL: Dynamic Brain Graph Structure Learning. CoRR abs/2209.13513 (2022) - [i132]Steve Azzolin, Antonio Longa, Pietro Barbiero, Pietro Liò, Andrea Passerini:
Global Explainability of GNNs via Logic Combination of Learned Concepts. CoRR abs/2210.07147 (2022) - [i131]Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, Tom L. Blundell, Pietro Lió, Carla Gomes, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Structure-based Drug Design with Equivariant Diffusion Models. CoRR abs/2210.13695 (2022) - [i130]Antonio Longa, Steve Azzolin, Gabriele Santin, Giulia Cencetti, Pietro Liò, Bruno Lepri, Andrea Passerini:
Explaining the Explainers in Graph Neural Networks: a Comparative Study. CoRR abs/2210.15304 (2022) - [i129]Fergus Imrie, Alexander Norcliffe, Pietro Liò, Mihaela van der Schaar:
Composite Feature Selection using Deep Ensembles. CoRR abs/2211.00631 (2022) - [i128]David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò:
Graph Neural Networks with Adaptive Readouts. CoRR abs/2211.04952 (2022) - [i127]Andrei Margeloiu, Nikola Simidjievski, Pietro Lio', Mateja Jamnik:
Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data. CoRR abs/2211.06302 (2022) - [i126]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. CoRR abs/2211.06885 (2022) - [i125]Carlos Purves, Pietro Liò, Catalina Cangea:
Goal-Conditioned Reinforcement Learning in the Presence of an Adversary. CoRR abs/2211.06929 (2022) - [i124]Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò:
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CoRR abs/2211.07650 (2022) - [i123]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. CoRR abs/2211.09732 (2022) - [i122]Yana Lishkova, Paul Scherer, Steffen Ridderbusch, Mateja Jamnik, Pietro Liò, Sina Ober-Blöbaum, Christian Offen:
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. CoRR abs/2211.10830 (2022) - [i121]Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng, Pietro Liò, Xiaowen Dong:
Transductive Kernels for Gaussian Processes on Graphs. CoRR abs/2211.15322 (2022) - [i120]Harrison Mitchell, Alexander Norcliffe, Pietro Liò:
Learning Feynman Diagrams using Graph Neural Networks. CoRR abs/2211.15348 (2022) - [i119]Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. CoRR abs/2211.15616 (2022) - [i118]Yu He, Petar Velickovic, Pietro Liò, Andreea Deac:
Continuous Neural Algorithmic Planners. CoRR abs/2211.15839 (2022) - [i117]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. CoRR abs/2211.16199 (2022) - [i116]Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Rex Ying, Jure Leskovec, Pietro Liò:
Learning Graph Search Heuristics. CoRR abs/2212.03978 (2022) - [i115]Aarjav Jain, Challenger Mishra, Pietro Liò:
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation. CoRR abs/2212.05892 (2022) - 2021
- [j103]Md. Rabiul Islam, Mohammad Ali Moni, Md. Milon Islam, Md Rashed-Al-Mahfuz, Md. Saiful Islam, Md. Kamrul Hasan, Md. Sabir Hossain, Mohiuddin Ahmad, Shahadat Uddin, A. K. M. Azad, Salem A. Alyami, Md. Atiqur Rahman Ahad, Pietro Lió:
Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques. IEEE Access 9: 94601-94624 (2021) - [j102]Zulkar Nain, Humayan Kabir Rana, Pietro Liò, Sheikh Mohammed Shariful Islam, Matthew A. Summers, Mohammad Ali Moni:
Pathogenetic profiling of COVID-19 and SARS-like viruses. Briefings Bioinform. 22(2): 1175-1196 (2021) - [j101]Kexin Chen, Haoming Xu, Yiming Lei, Pietro Lió, Yuan Li, Hongyan Guo, Mohammad Ali Moni:
Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance. Briefings Bioinform. 22(6) (2021) - [j100]Francesco Bardozzo, Pietro Lió, Roberto Tagliaferri:
Signal metrics analysis of oscillatory patterns in bacterial multi-omic networks. Bioinform. 37(10): 1411-1419 (2021) - [j99]Andrea Tangherloni, Federico Ricciuti, Daniela Besozzi, Pietro Liò, Ana Cvejic:
Analysis of single-cell RNA sequencing data based on autoencoders. BMC Bioinform. 22(1): 309 (2021) - [j98]Daniele D'Agostino, Pietro Liò, Marco Aldinucci, Ivan Merelli:
Advantages of using graph databases to explore chromatin conformation capture experiments. BMC Bioinform. 22-S(2): 43 (2021) - [j97]Cristian Bodnar, Catalina Cangea, Pietro Liò:
Deep Graph Mapper: Seeing Graphs Through the Neural Lens. Frontiers Big Data 4: 680535 (2021) - [j96]Jin Zhu, Chuan Tan, Junwei Yang, Guang Yang, Pietro Lio':
Arbitrary Scale Super-Resolution for Medical Images. Int. J. Neural Syst. 31(10): 2150037:1-2150037:20 (2021) - [j95]Mihaela van der Schaar, Ahmed M. Alaa, R. Andres Floto, Alexander Gimson, Stefan Scholtes, Angela M. Wood, Eoin F. McKinney, Daniel Jarrett, Pietro Lió, Ari Ercole:
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Mach. Learn. 110(1): 1-14 (2021) - [j94]Xiaofeng Lu, Songbing Fu, Cheng Jiang, Pietro Lió:
A Fine-Grained IoT Data Access Control Scheme Combining Attribute-Based Encryption and Blockchain. Secur. Commun. Networks 2021: 5308206:1-5308206:13 (2021) - [j93]Marialisa Scatà, Alessandro Di Stefano, Aurelio La Corte, Pietro Liò:
A Multiplex Social Contagion Dynamics Model to Shape and Discriminate D2D Content Dissemination. IEEE Trans. Cogn. Commun. Netw. 7(2): 581-593 (2021) - [c129]Emma Rocheteau, Pietro Liò, Stephanie L. Hyland:
Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit. CHIL 2021: 58-68 - [c128]Emanuele Bellini, Franco Bagnoli, Mauro Caporuscio, Ernesto Damiani, Francesco Flammini, Igor Linkov, Pietro Liò, Stefano Marrone:
Resilience learning through self adaptation in digital twins of human-cyber-physical systems. CSR 2021: 168-173 - [c127]Xiaofeng Lu, Pietro Liò:
International Workshop On Application of Intelligent Technology in Security - AITS 2021. DSN Workshops 2021: xiv-xv - [c126]Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò:
Neural ODE Processes. ICLR 2021 - [c125]Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió:
Directional Graph Networks. ICML 2021: 748-758 - [c124]Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICML 2021: 1026-1037 - [c123]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. ICML 2021: 12761-12771 - [c122]Nikola Zubic, Pietro Liò:
An Effective Loss Function for Generating 3D Models from Single 2D Image Without Rendering. AIAI 2021: 309-322 - [c121]Lorena Qendro, Alexander Campbell, Pietro Liò, Cecilia Mascolo:
Early Exit Ensembles for Uncertainty Quantification. ML4H@NeurIPS 2021: 181-195 - [c120]Isaac Sebenius, Alexander Campbell, Sarah E. Morgan, Edward T. Bullmore, Pietro Liò:
Multimodal Graph Coarsening for Interpretable, MRI-Based Brain Graph Neural Network. MLSP 2021: 1-6 - [c119]Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. NeurIPS 2021: 2625-2640 - [c118]Gabriele Corso, Zhitao Ying, Michal Pándy, Petar Velickovic, Jure Leskovec, Pietro Liò:
Neural Distance Embeddings for Biological Sequences. NeurIPS 2021: 18539-18551 - [i114]Emma Rocheteau, Catherine Tong, Petar Velickovic, Nicholas D. Lane, Pietro Liò:
Predicting Patient Outcomes with Graph Representation Learning. CoRR abs/2101.03940 (2021) - [i113]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. CoRR abs/2102.06986 (2021) - [i112]Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. CoRR abs/2103.03212 (2021) - [i111]Nikola Zubic, Pietro Liò:
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering. CoRR abs/2103.03390 (2021) - [i110]Alexander Norcliffe, Cristian Bodnar, Ben Day, Jacob Moss, Pietro Liò:
Neural ODE Processes. CoRR abs/2103.12413 (2021) - [i109]Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas D. Lane:
Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions. CoRR abs/2104.01481 (2021) - [i108]Dmitry Kazhdan, Botty Dimanov, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò, Adrian Weller:
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. CoRR abs/2104.06917 (2021) - [i107]Ben Day, Alexander Norcliffe, Jacob Moss, Pietro Liò:
Meta-learning using privileged information for dynamics. CoRR abs/2104.14290 (2021) - [i106]Jin Zhu, Chuan Tan, Junwei Yang, Guang Yang, Pietro Lio':
MIASSR: An Approach for Medical Image Arbitrary Scale Super-Resolution. CoRR abs/2105.10738 (2021) - [i105]Alice Del Vecchio, Andreea Deac, Pietro Liò, Petar Velickovic:
Neural message passing for joint paratope-epitope prediction. CoRR abs/2106.00757 (2021) - [i104]