2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching
Om Roy, Yashar Moshfeghi, Keith Malcolm Smith
High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, often low-rank covariance esti…
TVGL-CFM:Generating and Forecasting Time-Varying Trajectories of Dynamic Networks with Conditional Flow Matching
Om Roy, Yashar Moshfeghi, Keith Malcolm Smith
Many complex systems, including brain networks, financial markets, and gene-regulatory circuits, are better described by interaction structures that evolve over time than by a sing…
Graph Variate Neural Networks
Om Roy, Yashar Moshfeghi, Keith Smith
Modelling dynamically evolving spatio-temporal signals is a prominent challenge in the Graph Neural Network (GNN) literature. Notably, GNNs assume an existing underlying graph stru…
Covariance Density Neural Networks
Om Roy, Yashar Moshfeghi, Keith Smith
Graph neural networks have re-defined how we model and predict on network data but there lacks a consensus on choosing the correct underlying graph structure on which to model sign…