6 citations · 6 across the 14 of their papers we have counts for
4 papers · 2 filters
Bayesian Formulations for Graph Spectral Denoising
Sam Leone, Xingzhi Sun, Michael Perlmutter +1
Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as…
BLIS-Net: Classifying and Analyzing Signals on Graphs
Charles Xu, Laney Goldman, Valentina Guo +7
Graph neural networks (GNNs) have emerged as a powerful tool for tasks such as node classification and graph classification. However, much less work has been done on signal classif…
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis
Aarthi Venkat, Joyce Chew, Ferran Cardoso Rodriguez +3
Directed graphs are a natural model for many phenomena, in particular scientific knowledge graphs such as molecular interaction or chemical reaction networks that define cellular s…
DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms
Dhananjay Bhaskar, Xingzhi Sun, Yanlei Zhang +8
We present DYMAG, a graph neural network based on a novel form of message aggregation. Standard message-passing neural networks, which often aggregate local neighbors via mean-aggr…