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Graph Classification with GNNs: Optimisation, Representation and
  Inductive Bias

Graph Classification with GNNs: Optimisation, Representation and Inductive Bias

17 August 2024
P. Krishna Kumar a
H. G. Ramaswamy
ArXivPDFHTML

Papers citing "Graph Classification with GNNs: Optimisation, Representation and Inductive Bias"

3 / 3 papers shown
Title
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
172
1,778
0
02 Mar 2017
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
280
1,400
0
01 Dec 2016
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
142
602
0
14 Feb 2016
1