Search Results for author:
Found 4 papers, 3 papers with code
DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly
Reassembly tasks play a fundamental role in many fields and multiple approaches exist to solve specific reassembly problems.
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs
We introduce QuaterGCN, a spectral Graph Convolutional Network (GCN) with quaternion-valued weights at whose core lies the Quaternionic Laplacian, a quaternion-valued Laplacian matrix by whose proposal we generalize two widely-used Laplacian matrices: the classical Laplacian (defined for undirected graphs) and the complex-valued Sign-Magnetic Laplacian (proposed to handle digraphs with weights of arbitrary sign).
SigMaNet: One Laplacian to Rule Them All
$L^{\sigma}$ is also completely parameter-free, which is not the case of other Laplacian operators such as, e. g., the Magnetic Laplacian.
Listening to the city, attentively: A Spatio-Temporal Attention Boosted Autoencoder for the Short-Term Flow Prediction Problem
In recent years, studying and predicting alternative mobility (e. g., sharing services) patterns in urban environments has become increasingly important as accurate and timely information on current and future vehicle flows can successfully increase the quality and availability of transportation services.
