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Diverse Ensembles Improve Calibration

Diverse Ensembles Improve Calibration

8 July 2020
Asa Cooper Stickland
Iain Murray
    UQCV
    FedML
ArXivPDFHTML

Papers citing "Diverse Ensembles Improve Calibration"

16 / 16 papers shown
Title
Diversity inducing Information Bottleneck in Model Ensembles
Diversity inducing Information Bottleneck in Model Ensembles
Samarth Sinha
Homanga Bharadhwaj
Anirudh Goyal
Hugo Larochelle
Animesh Garg
Florian Shkurti
BDL
UQCV
49
40
0
10 Mar 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and
  Lifelong Learning
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning
Yeming Wen
Dustin Tran
Jimmy Ba
OOD
FedML
UQCV
149
491
0
17 Feb 2020
Self-training with Noisy Student improves ImageNet classification
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie
Minh-Thang Luong
Eduard H. Hovy
Quoc V. Le
NoLa
296
2,387
0
11 Nov 2019
Reducing Transformer Depth on Demand with Structured Dropout
Reducing Transformer Depth on Demand with Structured Dropout
Angela Fan
Edouard Grave
Armand Joulin
113
592
0
25 Sep 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
159
1,688
0
06 Jun 2019
CutMix: Regularization Strategy to Train Strong Classifiers with
  Localizable Features
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun
Dongyoon Han
Seong Joon Oh
Sanghyuk Chun
Junsuk Choe
Y. Yoo
OOD
604
4,766
0
13 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and
  Perturbations
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
Dan Hendrycks
Thomas G. Dietterich
OOD
VLM
158
3,423
0
28 Mar 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang
Kun Xu
Chao Du
Ning Chen
Jun Zhu
AAML
60
437
0
25 Jan 2019
Attention-based Ensemble for Deep Metric Learning
Attention-based Ensemble for Deep Metric Learning
Wonsik Kim
Bhavya Goyal
Kunal Chawla
Jungmin Lee
Keunjoo Kwon
FedML
68
227
0
02 Apr 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
271
9,743
0
25 Oct 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
280
5,812
0
14 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
743
5,798
0
05 Dec 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
288
8,091
0
13 Aug 2016
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles
Stefan Lee
Senthil Purushwalkam
Michael Cogswell
Viresh Ranjan
David J. Crandall
Dhruv Batra
BDL
UQCV
OOD
63
178
0
24 Jun 2016
Deep Networks with Stochastic Depth
Deep Networks with Stochastic Depth
Gao Huang
Yu Sun
Zhuang Liu
Daniel Sedra
Kilian Q. Weinberger
201
2,352
0
30 Mar 2016
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
243
19,017
0
20 Dec 2014
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