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Deep Confidence: A Computationally Efficient Framework for Calculating
  Reliable Errors for Deep Neural Networks

Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks

24 September 2018
I. Cortés-Ciriano
A. Bender
    OOD
    UQCV
ArXivPDFHTML

Papers citing "Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks"

12 / 12 papers shown
Title
Materials Property Prediction with Uncertainty Quantification: A
  Benchmark Study
Materials Property Prediction with Uncertainty Quantification: A Benchmark Study
Daniel Varivoda
Rongzhi Dong
Sadman Sadeed Omee
Jianjun Hu
AI4CE
28
20
0
04 Nov 2022
Drug discovery with explainable artificial intelligence
Drug discovery with explainable artificial intelligence
José Jiménez-Luna
F. Grisoni
G. Schneider
30
625
0
01 Jul 2020
Autonomous discovery in the chemical sciences part II: Outlook
Autonomous discovery in the chemical sciences part II: Outlook
Connor W. Coley
Natalie S. Eyke
K. Jensen
23
171
0
30 Mar 2020
Reliable Prediction Errors for Deep Neural Networks Using Test-Time
  Dropout
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout
I. Cortés-Ciriano
A. Bender
OOD
26
47
0
12 Apr 2019
KekuleScope: prediction of cancer cell line sensitivity and compound
  potency using convolutional neural networks trained on compound images
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images
I. Cortés-Ciriano
A. Bender
MedIm
24
51
0
22 Nov 2018
Constrained Bayesian Optimization for Automatic Chemical Design
Constrained Bayesian Optimization for Automatic Chemical Design
Ryan-Rhys Griffiths
José Miguel Hernández-Lobato
BDL
39
76
0
16 Sep 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
276
5,660
0
05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,889
0
15 Sep 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
197
745
0
06 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
UQCV
BDL
285
9,138
0
06 Jun 2015
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
Cross-conformal predictors
Cross-conformal predictors
V. Vovk
131
196
0
03 Aug 2012
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