CayleyNets : graph convolutional neural networks with complex rational spectral filters
The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has brought the interest in generalizing deep learning models to non-Euclidean domains. In...
Saved in:
Main Authors: | Levie, Ron, Monti, Federico, Bresson, Xavier, Bronstein, Michael M. |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139445 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Poisson kernel: avoiding self-smoothing in graph convolutional networks
by: Yang, Ziqing, et al.
Published: (2022) -
On Perfect Cayley Graphs
by: Garciano, Agnes, et al.
Published: (2002) -
When convolutional network meets temporal heterogeneous graphs: an effective community detection method
by: Zheng, Yaping, et al.
Published: (2023) -
A multisensory interaction framework for human-cyber–physical system based on graph convolutional networks
by: Qi, Wenqian, et al.
Published: (2024) -
DEEP LEARNING ON GRAPH-STRUCTURED DATA
by: TONG ZEKUN
Published: (2023)