6 citations · 6 across the 5 of their papers we have counts for
3 papers · 1 filter
DBGDGM: Dynamic Brain Graph Deep Generative Model
Alexander Campbell, Simeon Spasov, Nicola Toschi +1
Graphs are a natural representation of brain activity derived from functional magnetic imaging (fMRI) data. It is well known that clusters of anatomical brain regions, known as fun…
DynDepNet: Learning Time-Varying Dependency Structures from fMRI Data via Dynamic Graph Structure Learning
Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti +2
Graph neural networks (GNNs) have demonstrated success in learning representations of brain graphs derived from functional magnetic resonance imaging (fMRI) data. However, existing…
tvGP-VAE: Tensor-variate Gaussian Process Prior Variational Autoencoder
Alex Campbell, Pietro Liò
Variational autoencoders (VAEs) are a powerful class of deep generative latent variable model for unsupervised representation learning on high-dimensional data. To ensure computati…