Tiago Azevedo
Tiago Azevedo
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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
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts
T Azevedo, R de Jong, M Mattina, P Maji
arXiv preprint arXiv:2009.02967, 2020
JADE, TraSMAPI and SUMO: A tool-chain for simulating traffic light control
T Azevedo, PJM de Ara˙jo, RJF Rossetti, AP Rocha
Proceedings of the 8th International Workshop on Agents in Traffic andá…, 2014
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
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
Early downregulation of hsa-miR-144-3p in serum from drug-na´ve Parkinson’s disease patients
E Zago, A Dal Molin, GM Dimitri, L Xumerle, C Pirazzini, MG Bacalini, ...
Scientific reports 12 (1), 1330, 2022
Deep Learning Enables Fast and Accurate Imputation of Gene Expression
R Vi˝as, T Azevedo, ER Gamazon, P Li˛
Frontiers in Genetics 12, 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 iná…, 2020
Population graph GNNs for brain age prediction
K Stankeviciute, T Azevedo, A Campbell, R Bethlehem, P Lio
ICML Workshop on Graph Representation Learning and Beyond (GRL+), 17-83, 2020
Artificial intelligence for diagnosis and prognosis in neuroimaging for dementia; a systematic review
R Borchert, T Azevedo, A Badhwar, J Bernal, M Betts, R Bruffaerts, ...
medRxiv, 2021.12. 12.21267677, 2021
A deep spatiotemporal graph learning architecture for brain connectivity analysis
T Azevedo, L Passamonti, P Li˛, N Toschi
2020 42nd Annual International Conference of the IEEE Engineering iná…, 2020
Towards a predictive spatio-temporal representation of brain data
T Azevedo, L Passamonti, P Lio, N Toschi
arXiv preprint arXiv:2003.03290, 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 Technologiesá…, 2015
Multilayer modelling of the human transcriptome and biological mechanisms of complex diseases and traits
T Azevedo, GM Dimitri, P Liˇ, ER Gamazon
NPJ systems biology and applications 7 (1), 24, 2021
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 Visioná…, 2021
On Efficient Uncertainty Estimation for Resource-Constrained Mobile Applications
J Rock, T Azevedo, R de Jong, D Ruiz-Mu˝oz, P Maji
arXiv preprint arXiv:2111.09838, 2021
A machine learning tool for interpreting differences in cognition using brain features
T Azevedo, L Passamonti, P Liˇ, N Toschi
Artificial Intelligence Applications and Innovations: 15th IFIP WG 12.5á…, 2019
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 Modelingá…, 2015
Object Detection Network with Spatial Uncertainty
PP Maji, TML Azevedo
US Patent App. 17/179,806, 2022
Data-driven representations in brain science: modelling approaches in gene expression and neuroimaging domains
T Azevedo
University of Cambridge, 2022
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