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2305.12313
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When are ensembles really effective?
Neural Information Processing Systems (NeurIPS), 2023
21 May 2023
Ryan Theisen
Hyunsuk Kim
Yaoqing Yang
Liam Hodgkinson
Michael W. Mahoney
FedML
UQCV
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Papers citing
"When are ensembles really effective?"
10 / 10 papers shown
Single-Teacher View Augmentation: Boosting Knowledge Distillation via Angular Diversity
S. Yu
Dongjun Nam
Dina Katabi
Jeany Son
170
0
0
26 Oct 2025
Learning Task-Agnostic Representations through Multi-Teacher Distillation
Philippe Formont
Maxime Darrin
Banafsheh Karimian
Jackie Chi Kit Cheung
Eric Granger
Ismail Ben Ayed
Mohammadhadi Shateri
Pablo Piantanida
222
2
0
21 Oct 2025
A Model Zoo on Phase Transitions in Neural Networks
Konstantin Schurholt
Léo Meynent
Yefan Zhou
Haiquan Lu
Yaoqing Yang
Damian Borth
452
3
0
25 Apr 2025
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference
Jasmeet Kaur
BDL
UQCV
505
0
0
15 Mar 2025
Learning Ensembles of Vision-based Safety Control Filters
Ihab Tabbara
Hussein Sibai
393
3
0
02 Dec 2024
Theoretical Limitations of Ensembles in the Age of Overparameterization
Niclas Dern
John P. Cunningham
Geoff Pleiss
BDL
UQCV
436
3
0
21 Oct 2024
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
Haiquan Lu
Xiaotian Liu
Yefan Zhou
Qunli Li
Kurt Keutzer
Michael W. Mahoney
Yujun Yan
Huanrui Yang
Yaoqing Yang
304
3
0
17 Jul 2024
Are Ensembles Getting Better all the Time?
Pierre-Alexandre Mattei
Damien Garreau
OOD
FedML
601
5
0
29 Nov 2023
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding
CLEaR (CLEaR), 2023
Myrl G. Marmarelis
Greg Ver Steeg
Aram Galstyan
Fred Morstatter
CML
OOD
378
6
0
15 Jun 2023
Pathologies of Predictive Diversity in Deep Ensembles
Taiga Abe
E. Kelly Buchanan
Geoff Pleiss
John P. Cunningham
UQCV
438
21
0
01 Feb 2023
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