Petar Veličković
Petar Veličković
Research Scientist, DeepMind
Verified email at - Homepage
Cited by
Cited by
Graph Attention Networks
P Veličković, G Cucurull, A Casanova, A Romero, P Liò, Y Bengio
6th International Conference on Learning Representations (ICLR 2018), 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
Towards Sparse Hierarchical Graph Classifiers
C Cangea*, P Veličković*, N Jovanović, T Kipf, P Liò
arXiv preprint arXiv:1811.01287, 2018
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
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
Attentive cross-modal paratope prediction
A Deac, P Veličković, P Sormanni
Journal of Computational Biology, 2018
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
Neural Execution of Graph Algorithms
P Veličković, R Ying, M Padovano, R Hadsell, C Blundell
8th International Conference on Learning Representations (ICLR 2020), 2020
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data
P Veličković, L Karazija, ND Lane, S Bhattacharya, E Liberis, P Liò, ...
Proceedings of the 12th EAI International Conference on Pervasive Computing …, 2018
Deep learning for complete beginners: convolutional neural networks with keras
P Veličković
Retrieved from Data Science Course London: https://cambridgespark. com …, 2017
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
XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification
C Cangea, P Veličković, P Liò
IEEE transactions on neural networks and learning systems, 2019
Principal Neighbourhood Aggregation for Graph Nets
G Corso*, L Cavalleri*, D Beaini, P Liò, P Veličković
arXiv preprint arXiv:2004.05718, 2020
Multi-omics data integration using cross-modal neural networks
I Bica, P Veličković, H Xiao, P Liò
Proceedings of the 26th European Symposium on Artificial Neural Networks …, 2018
Molecular multiplex network inference using Gaussian mixture hidden Markov models
P Veličković, P Liò
Journal of Complex Networks 4 (4), 561-574, 2016
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
Spatio-Temporal Deep Graph Infomax
FL Opolka*, A Solomon*, C Cangea, P Veličković, P Liò, RD Hjelm
arXiv preprint arXiv:1904.06316, 2019
ChronoMID—Cross-modal neural networks for 3-D temporal medical imaging data
AG Rakowski, P Veličković, E Dall’Ara, P Liò
PloS one 15 (2), e0228962, 2020
Automatic inference of cross-modal connection topologies for x-cnns
L Karazija, P Veličković, P Liò
International Symposium on Neural Networks, 54-63, 2018
Scaling health analytics to millions without compromising privacy using deep distributed behavior models
P Veličković, ND Lane, S Bhattacharya, A Chieh, O Bellahsen, ...
Proceedings of the 11th EAI International Conference on Pervasive Computing …, 2017
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