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Simeon Spasov
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A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease
S Spasov, L Passamonti, A Duggento, P Lio, N Toschi, ...
Neuroimage 189, 276-287, 2019
409*2019
A multi-modal convolutional neural network framework for the prediction of Alzheimer’s disease
SE Spasov, L Passamonti, A Duggento, P Lio, N Toschi
2018 40th annual international conference of the IEEE engineering in …, 2018
872018
Multimodal and multicontrast image fusion via deep generative models
GM Dimitri, S Spasov, A Duggento, L Passamonti, P Lió, N Toschi
Information Fusion 88, 146-160, 2022
292022
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
292019
OptiJ: Open-source optical projection tomography of large organ samples
PP Vallejo Ramirez, J Zammit, O Vanderpoorten, F Riche, FX Blé, ...
Scientific reports 9 (1), 15693, 2019
272019
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
252022
Unsupervised stratification in neuroimaging through deep latent embeddings
GM Dimitri, S Spasov, A Duggento, L Passamonti, N Toschi
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
212020
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
172021
Dynamic Neural Network Channel Execution for Efficient Training
SE Spasov, P Liò
British Machine Vision Conference (BMVC), 2019
72019
Grade: Graph dynamic embedding
S Spasov, A Di Stefano, P Lio, J Tang
arXiv preprint arXiv:2007.08060, 2020
62020
RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow
S Glass, S Spasov, P Liò
7th ICML Workshop on Automated Machine Learning (AutoML), 2020
62020
Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making
D Taylor, S Spasov, P Liò
ML4H: Machine Learning for Health (NeurIPS), 2019
62019
Multimodal image fusion via deep generative models
GM Dimitri, S Spasov, A Duggento, L Passamonti, P Lio’, N Toschi
bioRxiv, 2021.03. 08.434427, 2021
22021
Neuroevolve: A dynamic brain graph deep generative model
SE Spasov, A Campbell, N Toschi, P Lio
ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH), 2023
12023
Dynamic Channel Execution: on-device Learning Method for Finding Compact Networks
SE Spasov, P Liò
EMC2: Workshop on Energy Efficient Machine Learning and Cognitive Computing …, 2019
12019
DBGDGM: Dynamic Brain Graph Deep Generative Model
A Campbell, S Spasov, N Toschi, P Lio
Medical Imaging with Deep Learning (MIDL) 2023 (Oral), 2023
2023
Encoding parameter and structural efficiency in deep learning
S Spasov
2022
TG-DGM: Clustering Brain Activity using a Temporal Graph Deep Generative Mode
SE Spasov, A Campbell, G Dimitri, A Di Stefano, F Scarselli, P Lio
Medical Imaging with Deep Learning 2021, 2021
2021
Multimodal image fusion via deep generative models
S Spasov, GM Dimitri
A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer’s disease within three years
S Spasov, L Passamonti, A Duggento, P Liò, R Way, RM Roma
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