Search Results for author: Luca Passamonti

Found 3 papers, 2 papers with code

Multimodal and multicontrast image fusion via deep generative models

no code implementations28 Mar 2023 Giovanna Maria Dimitri, Simeon Spasov, Andrea Duggento, Luca Passamonti, Pietro Li`o, Nicola Toschi

As proof of concept, we test our architecture on the well characterized Human Connectome Project database demonstrating that our latent embeddings can be clustered into easily separable subject strata which, in turn, map to different phenotypical information which was not included in the embedding creation process.

Dimensionality Reduction

DynDepNet: Learning Time-Varying Dependency Structures from fMRI Data via Dynamic Graph Structure Learning

2 code implementations27 Sep 2022 Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio

Graph neural networks (GNNs) have demonstrated success in learning representations of brain graphs derived from functional magnetic resonance imaging (fMRI) data.

Graph structure learning

Towards a predictive spatio-temporal representation of brain data

1 code implementation29 Feb 2020 Tiago Azevedo, Luca Passamonti, Pietro Liò, Nicola Toschi

The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph theory analyses, has been very popular in the last years.

Binary Classification

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