7 citations · 12 across the 3 of their papers we have counts for
4 papers
Topological Kalman Filtering on Cell Complexes
Chengen Liu, Rohan Money, Ting Gao +3
Inferring latent dynamics from multivariate time-series defined over topological cell complexes is crucial for capturing the complex, higher-order interactions inherent in real-wor…
GKNet: Graph Kalman Filtering and Model Inference via Model-based Deep Learning
Mohammad Sabbaqi, Riccardo Taormina, Elvin Isufi
Inference tasks with time series over graphs are of importance in applications such as urban water networks, economics, and networked neuroscience. Addressing these tasks typically…
Spatiotemporal Covariance Neural Networks
Andrea Cavallo, Mohammad Sabbaqi, Elvin Isufi
Modeling spatiotemporal interactions in multivariate time series is key to their effective processing, but challenging because of their irregular and often unknown structure. Stati…
Graph-Time Convolutional Neural Networks: Architecture and Theoretical Analysis
Mohammad Sabbaqi, Elvin Isufi
Devising and analyzing learning models for spatiotemporal network data is of importance for tasks including forecasting, anomaly detection, and multi-agent coordination, among othe…