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GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural
  Networks

GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks

7 March 2024
Lisa Schneckenreiter
Richard Freinschlag
Florian Sestak
Johannes Brandstetter
G. Klambauer
Andreas Mayr
ArXivPDFHTML

Papers citing "GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks"

6 / 6 papers shown
Title
BioX-CPath: Biologically-driven Explainable Diagnostics for Multistain IHC Computational Pathology
BioX-CPath: Biologically-driven Explainable Diagnostics for Multistain IHC Computational Pathology
Amaya Gallagher-Syed
Henry Senior
Omnia Alwazzan
Elena Pontarini
Michele Bombardieri
C. Pitzalis
M. Lewis
Michael Barnes
Luca Rossi
Gregory G. Slabaugh
38
0
0
26 Mar 2025
Sequential Signal Mixing Aggregation for Message Passing Graph Neural
  Networks
Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks
Mitchell Keren Taraday
Almog David
Chaim Baskin
26
0
0
28 Sep 2024
Principled Weight Initialisation for Input-Convex Neural Networks
Principled Weight Initialisation for Input-Convex Neural Networks
Pieter-Jan Hoedt
G. Klambauer
21
5
0
19 Dec 2023
Variational Annealing on Graphs for Combinatorial Optimization
Variational Annealing on Graphs for Combinatorial Optimization
Sebastian Sanokowski
Wilhelm Berghammer
Sepp Hochreiter
Sebastian Lehner
46
13
0
23 Nov 2023
Rapid training of deep neural networks without skip connections or
  normalization layers using Deep Kernel Shaping
Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping
James Martens
Andy Ballard
Guillaume Desjardins
G. Swirszcz
Valentin Dalibard
Jascha Narain Sohl-Dickstein
S. Schoenholz
83
43
0
05 Oct 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
172
1,100
0
27 Apr 2021
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