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Are Graph Neural Networks Miscalibrated?
v1v2 (latest)

Are Graph Neural Networks Miscalibrated?

7 May 2019
Leonardo Teixeira
B. Jalaeian
Bruno Ribeiro
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Are Graph Neural Networks Miscalibrated?"

12 / 12 papers shown
Title
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
Dingyi Zhuang
Chonghe Jiang
Yunhan Zheng
Shenhao Wang
Jinhua Zhao
UQCV
107
0
0
12 Oct 2024
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DHGNN3DPC
234
4,361
0
06 Mar 2019
Evaluating model calibration in classification
Evaluating model calibration in classification
Juozas Vaicenavicius
David Widmann
Carl R. Andersson
Fredrik Lindsten
Jacob Roll
Thomas B. Schon
UQCV
157
199
0
19 Feb 2019
Pitfalls of Graph Neural Network Evaluation
Pitfalls of Graph Neural Network Evaluation
Oleksandr Shchur
Maximilian Mumme
Aleksandar Bojchevski
Stephan Günnemann
GNN
168
1,364
0
14 Nov 2018
Janossy Pooling: Learning Deep Permutation-Invariant Functions for
  Variable-Size Inputs
Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
R. Murphy
Balasubramaniam Srinivasan
Vinayak A. Rao
Yun Liang
117
192
0
05 Nov 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
245
7,681
0
01 Oct 2018
Relational inductive biases, deep learning, and graph networks
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
V. Zambaldi
...
Pushmeet Kohli
M. Botvinick
Oriol Vinyals
Yujia Li
Razvan Pascanu
AI4CENAI
764
3,129
0
04 Jun 2018
Graph networks as learnable physics engines for inference and control
Graph networks as learnable physics engines for inference and control
Alvaro Sanchez-Gonzalez
N. Heess
Jost Tobias Springenberg
J. Merel
Martin Riedmiller
R. Hadsell
Peter W. Battaglia
GNNAI4CEPINNOCL
213
602
0
04 Jun 2018
Few-Shot Learning with Graph Neural Networks
Few-Shot Learning with Graph Neural Networks
Victor Garcia Satorras
Joan Bruna
GNN
172
1,240
0
10 Nov 2017
Learning Multiagent Communication with Backpropagation
Learning Multiagent Communication with Backpropagation
Sainbayar Sukhbaatar
Arthur Szlam
Rob Fergus
224
1,150
0
25 May 2016
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David Duvenaud
D. Maclaurin
J. Aguilera-Iparraguirre
Rafael Gómez-Bombarelli
Timothy D. Hirzel
Alán Aspuru-Guzik
Ryan P. Adams
GNN
223
3,353
0
30 Sep 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
836
9,345
0
06 Jun 2015
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