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Hamilton-Jacobi equations on graphs with applications to semi-supervised
  learning and data depth

Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth

17 February 2022
Jeff Calder
Mahmood Ettehad
ArXivPDFHTML

Papers citing "Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth"

5 / 5 papers shown
Title
A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs
A Learned Generalized Geodesic Distance Function-Based Approach for Node Feature Augmentation on Graphs
Amitoz Azad
Yuan Fang
32
1
0
01 Jul 2024
Choosing the parameter of the Fermat distance: navigating geometry and
  noise
Choosing the parameter of the Fermat distance: navigating geometry and noise
Frédéric Chazal
Laure Ferraris
Pablo Groisman
Matthieu Jonckheere
Frédéric Pascal
F. Sapienza
OT
8
0
0
30 Nov 2023
Models for information propagation on graphs
Models for information propagation on graphs
Oliver R. A. Dunbar
C. M. Elliott
L. Kreusser
11
2
0
19 Jan 2022
Eikonal depth: an optimal control approach to statistical depths
Eikonal depth: an optimal control approach to statistical depths
M. Molina-Fructuoso
Ryan W. Murray
MDE
20
4
0
14 Jan 2022
SPAGAN: Shortest Path Graph Attention Network
SPAGAN: Shortest Path Graph Attention Network
Yiding Yang
Xinchao Wang
Mingli Song
Junsong Yuan
Dacheng Tao
GNN
130
94
0
10 Jan 2021
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