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Preventing Representational Rank Collapse in MPNNs by Splitting the
  Computational Graph

Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph

17 September 2024
Andreas Roth
Franka Bause
Nils M. Kriege
Thomas Liebig
ArXivPDFHTML

Papers citing "Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph"

2 / 2 papers shown
Title
A Theory for Compressibility of Graph Transformers for Transductive
  Learning
A Theory for Compressibility of Graph Transformers for Transductive Learning
Hamed Shirzad
Honghao Lin
A. Velingker
B. Venkatachalam
David P. Woodruff
Danica J. Sutherland
72
1
0
20 Nov 2024
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum
  Properties for Improved ADMET Modeling
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modeling
Alessio Fallani
Ramil I. Nugmanov
Jose A. Arjona-Medina
Jörg Kurt Wegner
Alexandre Tkatchenko
Kostiantyn Chernichenko
MedIm
AI4CE
21
0
0
10 Oct 2024
1