ResearchTrend.AI
HoloNets: Spectral Convolutions do extend to Directed Graphs
v1v2 (latest)

HoloNets: Spectral Convolutions do extend to Directed Graphs

Christian Koke
Zorah Lähner
ArXiv (abs)PDFHTML

Papers citing "HoloNets: Spectral Convolutions do extend to Directed Graphs"

6 / 6 papers shown
Title
Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding
Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding
Manuel Lecha
Andrea Cavallo
Francesca Dominici
Ran Levi
Alessio Del Bue
Elvin Isufi
Pietro Morerio
Claudio Battiloro
AI4CE
111
0
0
23 May 2025
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Thomas Dagès
Simon Weber
Ya-Wei Eileen Lin
Ronen Talmon
Daniel Cremers
M. Lindenbaum
A. Bruckstein
Ron Kimmel
218
0
0
23 Mar 2025
Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach
Toward Effective Digraph Representation Learning: A Magnetic Adaptive Propagation based Approach
Miao Hu
Daohan Su
Zhengyu Wu
Guang Zeng
Hongchao Qin
Rong-Hua Li
Guoren Wang
AI4CE
121
0
0
21 Jan 2025
A Benchmark on Directed Graph Representation Learning in Hardware Designs
A Benchmark on Directed Graph Representation Learning in Hardware Designs
Haoyu Wang
Yinan Huang
Nan Wu
Pan Li
OOD
136
1
0
09 Oct 2024
Commute Graph Neural Networks
Commute Graph Neural Networks
Wei Zhuo
Han Yu
Guang Tan
Xiaoxiao Li
GNN
197
1
0
30 Jun 2024
Adaptive Universal Generalized PageRank Graph Neural Network
Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien
Jianhao Peng
Pan Li
O. Milenkovic
303
751
0
14 Jun 2020

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.