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Towards Interpretable Sparse Graph Representation Learning with
  Laplacian Pooling

Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling

28 May 2019
Emmanuel Noutahi
Dominique Beaini
Julien Horwood
Sébastien Giguère
Prudencio Tossou
    AI4CE
ArXivPDFHTML

Papers citing "Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling"

12 / 12 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
41
0
0
26 Mar 2025
Hierarchical Graph Pooling is an Effective Citywide Traffic Condition
  Prediction Model
Hierarchical Graph Pooling is an Effective Citywide Traffic Condition Prediction Model
Shilin Pu
Liang Chu
Zhuoran Hou
Jincheng Hu
Yanjun Huang
Yuanjian Zhang
219
0
0
08 Sep 2022
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation
  Metrics
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Yiqiao Li
Jianlong Zhou
Sunny Verma
Fang Chen
XAI
34
39
0
26 Jul 2022
Interpretable Molecular Graph Generation via Monotonic Constraints
Interpretable Molecular Graph Generation via Monotonic Constraints
Yuanqi Du
Xiaojie Guo
Amarda Shehu
Liang Zhao
63
19
0
28 Feb 2022
Understanding Pooling in Graph Neural Networks
Understanding Pooling in Graph Neural Networks
Daniele Grattarola
Daniele Zambon
F. Bianchi
Cesare Alippi
GNN
FAtt
AI4CE
30
90
0
11 Oct 2021
A Systematic Survey on Deep Generative Models for Graph Generation
A Systematic Survey on Deep Generative Models for Graph Generation
Xiaojie Guo
Liang Zhao
MedIm
44
147
0
13 Jul 2020
Principal Neighbourhood Aggregation for Graph Nets
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso
Luca Cavalleri
Dominique Beaini
Pietro Lió
Petar Velickovic
GNN
27
651
0
12 Apr 2020
Disentangling Interpretable Generative Parameters of Random and
  Real-World Graphs
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs
Niklas Stoehr
Emine Yilmaz
Marc Brockschmidt
Jan Stuehmer
BDL
CML
DRL
22
14
0
12 Oct 2019
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation
  Models
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Daniil Polykovskiy
Alexander Zhebrak
Benjamín Sánchez-Lengeling
Sergey Golovanov
Oktai Tatanov
...
Simon Johansson
Hongming Chen
Sergey I. Nikolenko
Alán Aspuru-Guzik
Alex Zhavoronkov
ELM
194
633
0
29 Nov 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph
  Generation
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
203
885
0
07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,340
0
12 Feb 2018
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
181
1,778
0
02 Mar 2017
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