SAE: Single Architecture Ensemble Neural Networks

SAE: Single Architecture Ensemble Neural Networks

9 February 2024

Miguel R. D. Rodrigues

Papers citing "SAE: Single Architecture Ensemble Neural Networks"

17 / 17 papers shown

Title
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 229 1,149 0 07 Jul 2021
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions Stefanos Laskaridis Alexandros Kouris Nicholas D. Lane TPM 102 116 0 09 Jun 2021
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges Yoshitomo Matsubara Marco Levorato Francesco Restuccia 77 207 0 08 Mar 2021
Training independent subnetworks for robust prediction Marton Havasi Rodolphe Jenatton Stanislav Fort Jeremiah Zhe Liu Jasper Snoek Balaji Lakshminarayanan Andrew M. Dai Dustin Tran UQCV OOD 85 213 0 13 Oct 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 76 101 0 15 Jun 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 55 213 0 14 May 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 162 493 0 17 Feb 2020
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 121 628 0 05 Dec 2019
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 167 1,695 0 06 Jun 2019
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement W. Kool H. V. Hoof Max Welling 118 219 0 14 Mar 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 186 773 0 12 Nov 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 216 652 0 03 Aug 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 199 4,355 0 24 Jun 2018
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 330 8,130 0 13 Aug 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 282 4,793 0 04 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,305 0 11 Feb 2015

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