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Ensemble Distribution Distillation
v1v2v3 (latest)

Ensemble Distribution Distillation

30 April 2019
A. Malinin
Bruno Mlodozeniec
Mark Gales
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Ensemble Distribution Distillation"

28 / 28 papers shown
Title
Quantifying Knowledge Distillation Using Partial Information Decomposition
Quantifying Knowledge Distillation Using Partial Information Decomposition
Pasan Dissanayake
Faisal Hamman
Barproda Halder
Ilia Sucholutsky
Qiuyi Zhang
Sanghamitra Dutta
79
1
0
12 Nov 2024
Uncertainty in Gradient Boosting via Ensembles
Uncertainty in Gradient Boosting via Ensembles
Aleksei Ustimenko
Liudmila Prokhorenkova
A. Malinin
UQCV
73
95
0
18 Jun 2020
Efficient Evaluation-Time Uncertainty Estimation by Improved
  Distillation
Efficient Evaluation-Time Uncertainty Estimation by Improved Distillation
Erik Englesson
Hossein Azizpour
UQCV
63
8
0
12 Jun 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
183
1,702
0
06 Jun 2019
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty
  and Adversarial Robustness
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
A. Malinin
Mark Gales
UQCVAAML
75
177
0
31 May 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning
A Simple Baseline for Bayesian Uncertainty in Deep Learning
Wesley J. Maddox
T. Garipov
Pavel Izmailov
Dmitry Vetrov
A. Wilson
BDLUQCV
96
809
0
07 Feb 2019
Improving Confidence Estimates for Unfamiliar Examples
Improving Confidence Estimates for Unfamiliar Examples
Zhizhong Li
Derek Hoiem
55
9
0
09 Apr 2018
Understanding Measures of Uncertainty for Adversarial Example Detection
Understanding Measures of Uncertainty for Adversarial Example Detection
Lewis Smith
Y. Gal
UQCV
94
365
0
22 Mar 2018
Predictive Uncertainty Estimation via Prior Networks
Predictive Uncertainty Estimation via Prior Networks
A. Malinin
Mark Gales
UDBDLEDLUQCVPER
193
923
0
28 Feb 2018
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
T. Garipov
Pavel Izmailov
Dmitrii Podoprikhin
Dmitry Vetrov
A. Wilson
UQCV
89
757
0
27 Feb 2018
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and
  Risk-sensitive Learning
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Stefan Depeweg
José Miguel Hernández-Lobato
Finale Doshi-Velez
Steffen Udluft
UQCVPERBDLUD
70
27
0
19 Oct 2017
Learning to Generate Long-term Future via Hierarchical Prediction
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas
Jimei Yang
Yuliang Zou
Sungryull Sohn
Xunyu Lin
Honglak Lee
77
380
0
19 Apr 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
UQCVBDL
842
5,841
0
05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
168
3,472
0
07 Oct 2016
Concrete Problems in AI Safety
Concrete Problems in AI Safety
Dario Amodei
C. Olah
Jacob Steinhardt
Paul Christiano
John Schulman
Dandelion Mané
242
2,404
0
21 Jun 2016
Deep Exploration via Bootstrapped DQN
Deep Exploration via Bootstrapped DQN
Ian Osband
Charles Blundell
Alexander Pritzel
Benjamin Van Roy
123
1,313
0
15 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,426
0
10 Dec 2015
Distilling Model Knowledge
Distilling Model Knowledge
George Papamakarios
BDL
51
17
0
08 Oct 2015
Bayesian Dark Knowledge
Bayesian Dark Knowledge
Masashi Sugiyama
Vivek Rathod
R. Garnett
Max Welling
BDLUQCV
83
259
0
14 Jun 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning
  with Humans in the Loop
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Feng Yu
Ari Seff
Yinda Zhang
Shuran Song
Thomas Funkhouser
Jianxiong Xiao
107
2,346
0
10 Jun 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
852
9,346
0
06 Jun 2015
Fast R-CNN
Fast R-CNN
Ross B. Girshick
ObjD
309
25,081
0
30 Apr 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
389
13,145
0
12 Mar 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
364
19,733
0
09 Mar 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,312
0
22 Dec 2014
Deep Speech: Scaling up end-to-end speech recognition
Deep Speech: Scaling up end-to-end speech recognition
Awni Y. Hannun
Carl Case
Jared Casper
Bryan Catanzaro
G. Diamos
...
R. Prenger
S. Satheesh
Shubho Sengupta
Adam Coates
A. Ng
188
2,128
0
17 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,508
0
04 Sep 2014
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
684
31,544
0
16 Jan 2013
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