Integration of machine learning methods to dissect genetically imputed transcriptomic profiles in Alzheimer’s disease C Maj, T Azevedo, V Giansanti, O Borisov, GM Dimitri, S Spasov, ... Frontiers in genetics 10, 726, 2019 | 17 | 2019 |
JADE, TraSMAPI and SUMO: A tool-chain for simulating traffic light control T Azevedo, PJM de Araújo, RJF Rossetti, AP Rocha Proceedings of the 8th International Workshop on Agents in Traffic and …, 2014 | 16 | 2014 |
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts T Azevedo, R de Jong, M Mattina, P Maji arXiv preprint arXiv:2009.02967, 2020 | 15 | 2020 |
A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data T Azevedo, A Campbell, R Romero-Garcia, L Passamonti, RAI Bethlehem, ... Medical Image Analysis 79, 102471, 2022 | 12 | 2022 |
A geroscience approach for Parkinson’s disease: Conceptual framework and design of PROPAG-AGEING project C Pirazzini, T Azevedo, L Baldelli, A Bartoletti-Stella, ... Mechanisms of Ageing and Development 194, 111426, 2021 | 11 | 2021 |
Deep Learning Enables Fast and Accurate Imputation of Gene Expression R Viñas, T Azevedo, ER Gamazon, P Liò Frontiers in Genetics 12, 2021 | 9* | 2021 |
A novel Graph Attention Network Architecture for modeling multimodal brain connectivity AC Filip, T Azevedo, L Passamonti, N Toschi, P Lio 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 9 | 2020 |
Towards a predictive spatio-temporal representation of brain data T Azevedo, L Passamonti, P Lio, N Toschi arXiv preprint arXiv:2003.03290, 2020 | 8 | 2020 |
A State-of-the-art Integrated Transportation Simulation Platform T Azevedo, RJF Rossetti, JG Barbosa Proceedings of the 4th International Conference on Models and Technologies …, 2015 | 8 | 2015 |
Early downregulation of hsa-miR-144-3p in serum from drug-naïve Parkinson’s disease patients E Zago, A Dal Molin, GM Dimitri, L Xumerle, C Pirazzini, MG Bacalini, ... Scientific reports 12 (1), 1330, 2022 | 7 | 2022 |
A deep spatiotemporal graph learning architecture for brain connectivity analysis T Azevedo, L Passamonti, P Liò, N Toschi 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 6 | 2020 |
Multilayer modelling of the human transcriptome and biological mechanisms of complex diseases and traits T Azevedo, GM Dimitri, P Lió, ER Gamazon npj Systems Biology and Applications 7 (1), 1-13, 2021 | 5 | 2021 |
Artificial intelligence for diagnosis and prognosis in neuroimaging for dementia; a systematic review RJ Borchert, T Azevedo, A Badhwar, J Bernal, M Betts, R Bruffaerts, ... medRxiv, 2021 | 5 | 2021 |
Population Graph GNNs for Brain Age Prediction K Stankevičiūtė, T Azevedo, A Campbell, RAI Bethlehem, P Liò bioRxiv, 2020 | 4 | 2020 |
A machine learning tool for interpreting differences in cognition using brain features T Azevedo, L Passamonti, P Lió, N Toschi IFIP International Conference on Artificial Intelligence Applications and …, 2019 | 4 | 2019 |
On Efficient Uncertainty Estimation for Resource-Constrained Mobile Applications J Rock, T Azevedo, R de Jong, D Ruiz-Muñoz, P Maji arXiv preprint arXiv:2111.09838, 2021 | 3 | 2021 |
Densifying the Sparse Cloud SimSaaS: The need of a Synergy among Agent-directed Simulation, SimSaaS and HLA T Azevedo, RJF Rossetti, JG Barbosa Proceedings of the 5th International Conference on Simulation and Modeling …, 2015 | 3 | 2015 |
Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification SA Tailor, R de Jong, T Azevedo, M Mattina, P Maji Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
Object Detection Network with Spatial Uncertainty PP Maji, TML Azevedo US Patent App. 17/179,806, 2022 | | 2022 |
Data-driven representations in brain science: modelling approaches in gene expression and neuroimaging domains T Azevedo University of Cambridge, 2022 | | 2022 |