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MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning

MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning

4 June 2024
Shay Deutsch
Lionel Yelibi
Alex Tong Lin
Arjun Ravi Kannan
ArXivPDFHTML

Papers citing "MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning"

2 / 2 papers shown
Title
MBExplainer: Multilevel bandit-based explanations for downstream models
  with augmented graph embeddings
MBExplainer: Multilevel bandit-based explanations for downstream models with augmented graph embeddings
Ashkan Golgoon
Ryan Franks
Khashayar Filom
Arjun Ravi Kannan
33
0
0
01 Nov 2024
Residual2Vec: Debiasing graph embedding with random graphs
Residual2Vec: Debiasing graph embedding with random graphs
Sadamori Kojaku
Jisung Yoon
I. Constantino
Yong-Yeol Ahn
CML
35
23
0
14 Oct 2021
1