| Graph Attention Networks P Veličković, G Cucurull, A Casanova, A Romero, P Liò, Y Bengio 6th International Conference on Learning Representations (ICLR 2018), 2018 | 9098* | 2018 |
| Deep Graph Infomax P Veličković, W Fedus, WL Hamilton, P Liò, Y Bengio, RD Hjelm 7th International Conference on Learning Representations (ICLR 2019), 2019 | 936* | 2019 |
| Geometric deep learning: Grids, groups, graphs, geodesics, and gauges MM Bronstein, J Bruna, T Cohen, P Veličković arXiv preprint arXiv:2104.13478, 2021 | 277 | 2021 |
| Principal neighbourhood aggregation for graph nets G Corso*, L Cavalleri*, D Beaini, P Liò, P Veličković Advances in Neural Information Processing Systems 33, 2020 | 209 | 2020 |
| Towards Sparse Hierarchical Graph Classifiers C Cangea*, P Veličković*, N Jovanović, T Kipf, P Liò arXiv preprint arXiv:1811.01287, 2018 | 162 | 2018 |
| Neural Execution of Graph Algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell 8th International Conference on Learning Representations (ICLR 2020), 2020 | 93 | 2020 |
| Combinatorial optimization and reasoning with graph neural networks Q Cappart, D Chételat, E Khalil, A Lodi, C Morris, P Veličković arXiv preprint arXiv:2102.09544, 2021 | 92 | 2021 |
| Advancing mathematics by guiding human intuition with AI A Davies, P Veličković, L Buesing, S Blackwell, D Zheng, N Tomašev, ... Nature 600 (7887), 70-74, 2021 | 89 | 2021 |
| Parapred: antibody paratope prediction using convolutional and recurrent neural networks E Liberis, P Veličković, P Sormanni, M Vendruscolo, P Liò Bioinformatics 34 (17), 2944-2950, 2018 | 79 | 2018 |
| Large-Scale Representation Learning on Graphs via Bootstrapping S Thakoor, C Tallec, MG Azar, M Azabou, EL Dyer, R Munos, P Veličković, ... 10th International Conference on Learning Representations (ICLR 2022), 2022 | 61* | 2022 |
| Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices A Mathur, T Zhang, S Bhattacharya, P Velickovic, L Joffe, ND Lane, ... 2018 17th ACM/IEEE International Conference on Information Processing in …, 2018 | 46 | 2018 |
| Attentive cross-modal paratope prediction A Deac, P Veličković, P Sormanni Journal of Computational Biology, 2018 | 38 | 2018 |
| Eta prediction with graph neural networks in google maps A Derrow-Pinion, J She, D Wong, O Lange, T Hester, L Perez, ... Proceedings of the 30th ACM International Conference on Information …, 2021 | 36 | 2021 |
| X-CNN: Cross-modal convolutional neural networks for sparse datasets P Veličković, D Wang, ND Lane, P Liò 2016 IEEE symposium series on computational intelligence (SSCI), 1-8, 2016 | 34 | 2016 |
| On the role of planning in model-based deep reinforcement learning JB Hamrick, AL Friesen, F Behbahani, A Guez, F Viola, S Witherspoon, ... 9th International Conference on Learning Representations (ICLR 2021), 2021 | 31 | 2021 |
| Drug-drug adverse effect prediction with graph co-attention A Deac, YH Huang, P Veličković, P Liò, J Tang arXiv preprint arXiv:1905.00534, 2019 | 30 | 2019 |
| Pointer graph networks P Veličković, L Buesing, MC Overlan, R Pascanu, O Vinyals, C Blundell Advances in Neural Information Processing Systems 33, 2020 | 27* | 2020 |
| Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond J Godwin, M Schaarschmidt, AL Gaunt, A Sanchez-Gonzalez, ... 10th International Conference on Learning Representations (ICLR 2022), 2022 | 26* | 2022 |
| Convolutional neural networks for mesh-based parcellation of the cerebral cortex G Cucurull, K Wagstyl, A Casanova, P Veličković, E Jakobsen, ... 1st International Conference on Medical Imaging with Deep Learning (MIDL 2018), 2018 | 25 | 2018 |
| Jraph: A library for graph neural networks in JAX J Godwin, T Keck, P Battaglia, V Bapst, T Kipf, Y Li, K Stachenfeld, ... URL http://github. com/deepmind/jraph, 2020 | 21* | 2020 |
P. Lió, Pietro Lio, P. Lio, Pietro Liò, Pie...University of CambridgeVerified email at cam.ac.uk
