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GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks

12 October 2024

Papers citing "GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks"

33 / 33 papers shown

Title
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration Siguang Huang Yunli Wang Lili Mou Huayue Zhang Ziru Xu Chuan Yu Bo Zheng 178 15 0 13 Mar 2025
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks Dingyi Zhuang Yuheng Bu Guang Wang Shenhao Wang Jinhua Zhao BDL 71 1 0 13 Sep 2024
SimCalib: Graph Neural Network Calibration based on Similarity between Nodes Boshi Tang Zhiyong Wu Xixin Wu Qiaochu Huang Jun Chen Shunwei Lei Helen M. Meng 77 8 0 19 Dec 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks Kexin Huang Ying Jin Emmanuel Candès J. Leskovec 217 63 0 23 May 2023
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling Haotao Wang Ziyu Jiang Yuning You Yan Han Gaowen Liu Jayanth Srinivasa Ramana Rao Kompella Zhangyang Wang 82 36 0 06 Apr 2023
What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu Yuesong Shen Christian Tomani Daniel Cremers 77 40 0 12 Oct 2022
Uncovering the Structural Fairness in Graph Contrastive Learning Ruijia Wang Xiao Wang Chuan Shi Le Song 153 35 0 06 Oct 2022
Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors Gianluca Detommaso Alberto Gasparin A. Wilson Cédric Archambeau UQCV BDL 60 3 0 17 Jul 2022
Better Uncertainty Calibration via Proper Scores for Classification and Beyond Sebastian G. Gruber Florian Buettner UQCV 73 50 0 15 Mar 2022
RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network Jian Kang Yangchun Zhu Yinglong Xia Jiebo Luo Hanghang Tong FaML 53 46 0 28 Feb 2022
Online Calibrated and Conformal Prediction Improves Bayesian Optimization Shachi Deshpande Charles Marx Volodymyr Kuleshov 47 8 0 08 Dec 2021
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration Xiao Wang Hongrui Liu Chuan Shi Cheng Yang UQCV 166 121 0 29 Sep 2021
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung Willie Neiswanger I. Char J. Schneider UQCV 169 88 0 18 Nov 2020
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 153 1,230 0 04 Nov 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Dmitry Lepikhin HyoukJoong Lee Yuanzhong Xu Dehao Chen Orhan Firat Yanping Huang M. Krikun Noam M. Shazeer Zhiwen Chen MoE 103 1,184 0 30 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 306 2,732 0 02 May 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 85 227 0 16 Mar 2020
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 73 381 0 28 Oct 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 167 357 0 23 Sep 2019
Are Graph Neural Networks Miscalibrated? Leonardo Teixeira B. Jalaeian Bruno Ribeiro AI4CE 55 22 0 07 May 2019
Graph Neural Networks for Social Recommendation Wenqi Fan Yao Ma Qing Li Yuan He Yue Zhao Jiliang Tang Dawei Yin 250 1,898 0 19 Feb 2019
Pitfalls of Graph Neural Network Evaluation Oleksandr Shchur Maximilian Mumme Aleksandar Bojchevski Stephan Günnemann GNN 168 1,360 0 14 Nov 2018
Session-based Recommendation with Graph Neural Networks Shu Wu Yuyuan Tang Yanqiao Zhu Liang Wang Xing Xie Tieniu Tan GNN 72 1,560 0 01 Nov 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 243 7,681 0 01 Oct 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 196 634 0 01 Jul 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 185 1,000 0 05 Jun 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,164 0 30 Oct 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,855 0 14 Jun 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 509 15,300 0 07 Jun 2017
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Noam M. Shazeer Azalia Mirhoseini Krzysztof Maziarz Andy Davis Quoc V. Le Geoffrey E. Hinton J. Dean MoE 251 2,653 0 23 Jan 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 644 29,076 0 09 Sep 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 829 9,345 0 06 Jun 2015
Binary Classifier Calibration: Non-parametric approach Mahdi Pakdaman Naeini G. Cooper Milos Hauskrecht 80 17 0 14 Jan 2014