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What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
v1v2 (latest)

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

15 March 2017
Alex Kendall
Y. Gal
    BDLOODUDUQCVPER
ArXiv (abs)PDFHTML

Papers citing "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"

50 / 2,432 papers shown
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Generative Probabilistic Novelty Detection with Adversarial AutoencodersNeural Information Processing Systems (NeurIPS), 2018
Stanislav Pidhorskyi
Ranya Almohsen
Donald Adjeroh
Gianfranco Doretto
UQCV
296
337
0
06 Jul 2018
Direct Uncertainty Prediction for Medical Second Opinions
Direct Uncertainty Prediction for Medical Second OpinionsInternational Conference on Machine Learning (ICML), 2018
M. Raghu
Katy Blumer
Rory Sayres
Ziad Obermeyer
Robert D. Kleinberg
S. Mullainathan
Jon M. Kleinberg
OODUD
449
144
0
04 Jul 2018
Leveraging Uncertainty Estimates for Predicting Segmentation Quality
Leveraging Uncertainty Estimates for Predicting Segmentation Quality
Terrance Devries
Graham W. Taylor
UQCV
244
119
0
02 Jul 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression
Accurate Uncertainties for Deep Learning Using Calibrated RegressionInternational Conference on Machine Learning (ICML), 2018
Volodymyr Kuleshov
Nathan Fenner
Stefano Ermon
BDLUQCV
569
741
0
01 Jul 2018
Towards safe deep learning: accurately quantifying biomarker uncertainty
  in neural network predictions
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions
Zach Eaton-Rosen
Felix J. S. Bragman
Sotirios Bisdas
Sebastien Ourselin
M. Jorge Cardoso
UQCV
113
92
0
22 Jun 2018
Bayesian Prediction of Future Street Scenes through Importance Sampling based Optimization
Apratim Bhattacharyya
Mario Fritz
Bernt Schiele
UQCVBDL
163
2
0
18 Jun 2018
Uncertainty in multitask learning: joint representations for
  probabilistic MR-only radiotherapy planning
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Felix J. S. Bragman
Ryutaro Tanno
Zach Eaton-Rosen
Wenqi Li
D. Hawkes
Sebastien Ourselin
Daniel C. Alexander
J. McClelland
M. Jorge Cardoso
UQCV
136
52
0
18 Jun 2018
On Machine Learning and Structure for Mobile Robots
On Machine Learning and Structure for Mobile Robots
Markus Wulfmeier
130
5
0
15 Jun 2018
Uncertainty Estimations by Softplus normalization in Bayesian
  Convolutional Neural Networks with Variational Inference
Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational Inference
Kumar Shridhar
F. Laumann
Marcus Liwicki
BDLUQCV
318
19
0
15 Jun 2018
Efficient Active Learning for Image Classification and Segmentation
  using a Sample Selection and Conditional Generative Adversarial Network
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network
Dwarikanath Mahapatra
Behzad Bozorgtabar
Jean-Philippe Thiran
M. Reyes
GANMedIm
302
189
0
14 Jun 2018
A Probabilistic U-Net for Segmentation of Ambiguous Images
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon A. A. Kohl
Bernardino Romera-Paredes
Clemens Meyer
J. Fauw
J. Ledsam
Klaus H. Maier-Hein
S. M. Ali Eslami
Danilo Jimenez Rezende
Olaf Ronneberger
UQCVSSeg
265
651
0
13 Jun 2018
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with
  Deep Learning
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning
A. Hess
Raphael Meier
Johannes Kaesmacher
Simon Jung
Fabien Scalzo
D. Liebeskind
Roland Wiest
Richard McKinley
MedIm
124
15
0
11 Jun 2018
Robust Semantic Segmentation with Ladder-DenseNet Models
Robust Semantic Segmentation with Ladder-DenseNet Models
Ivan Kreso
Marin Orsic
Petra Bevandić
Sinisa Segvic
SSeg
101
12
0
09 Jun 2018
Uncertainty-driven Sanity Check: Application to Postoperative Brain
  Tumor Cavity Segmentation
Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation
Alain Jungo
Raphael Meier
E. Ermiş
Evelyn Herrmann
M. Reyes
UQCV
184
48
0
08 Jun 2018
On the Effect of Inter-observer Variability for a Reliable Estimation of
  Uncertainty of Medical Image Segmentation
On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation
Alain Jungo
Raphael Meier
E. Ermiş
Marcela Blatti-Moreno
Evelyn Herrmann
Roland Wiest
M. Reyes
UQCV
117
111
0
07 Jun 2018
Deep Ordinal Regression Network for Monocular Depth Estimation
Deep Ordinal Regression Network for Monocular Depth Estimation
Huan Fu
Biwei Huang
Chaohui Wang
Kayhan Batmanghelich
Dacheng Tao
MDE
926
1,896
0
06 Jun 2018
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance
  Segmentation in Colon Histology Images
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images
S. Graham
Hao Chen
Jevgenij Gamper
Qi Dou
Pheng-Ann Heng
David R. J. Snead
Yee Wah Tsang
Nasir M. Rajpoot
MedIm
259
341
0
05 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy
Lance M. Kaplan
M. Kandemir
OODUQCVEDLBDL
723
1,273
0
05 Jun 2018
Sufficient Conditions for Idealised Models to Have No Adversarial
  Examples: a Theoretical and Empirical Study with Bayesian Neural Networks
Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks
Y. Gal
Lewis Smith
AAMLBDL
225
35
0
02 Jun 2018
To Trust Or Not To Trust A Classifier
To Trust Or Not To Trust A Classifier
Heinrich Jiang
Been Kim
Melody Y. Guan
Maya R. Gupta
UQCV
470
494
0
30 May 2018
Uncertainty Gated Network for Land Cover Segmentation
Uncertainty Gated Network for Land Cover Segmentation
Guillem Pascual
Santi Seguí
Jordi Vitrià
UQCV
111
11
0
29 May 2018
Lightweight Probabilistic Deep Networks
Lightweight Probabilistic Deep Networks
Jochen Gast
Stefan Roth
UQCVOODBDL
257
196
0
29 May 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated
  Classification
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
Dimitrios Milios
Raffaello Camoriano
Pietro Michiardi
Lorenzo Rosasco
Maurizio Filippone
UQCV
189
82
0
28 May 2018
Calibrating Deep Convolutional Gaussian Processes
Calibrating Deep Convolutional Gaussian Processes
Gia-Lac Tran
Edwin V. Bonilla
John P. Cunningham
Pietro Michiardi
Maurizio Filippone
BDLUQCV
150
44
0
26 May 2018
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo
Haebeom Lee
Saehoon Kim
Juho Lee
Kwang Joon Kim
Eunho Yang
Sung Ju Hwang
OOD
170
92
0
24 May 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by
  Variance Backpropagation
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation
Manuel Haussmann
Fred Hamprecht
M. Kandemir
BDL
146
6
0
19 May 2018
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided
  Mixture Density Networks
Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks
Sungjoon Choi
Sanghoon Hong
Kyungjae Lee
Sungbin Lim
OOD
251
8
0
16 May 2018
Confidence Scoring Using Whitebox Meta-models with Linear Classifier
  Probes
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes
Tongfei Chen
Jirí Navrátil
Vijay Iyengar
Karthikeyan Shanmugam
154
48
0
14 May 2018
Spatial Uncertainty Sampling for End-to-End Control
Spatial Uncertainty Sampling for End-to-End Control
Alexander Amini
A. Soleimany
S. Karaman
Daniela Rus
UQCVBDL
115
33
0
13 May 2018
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View
  Depth Predictors as Priors
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors
C. Weerasekera
Thanuja Dharmasiri
Ravi Garg
Tom Drummond
Ian Reid
140
27
0
11 May 2018
Loss-Calibrated Approximate Inference in Bayesian Neural Networks
Loss-Calibrated Approximate Inference in Bayesian Neural Networks
Adam D. Cobb
Stephen J. Roberts
Y. Gal
BDLUQCV
156
45
0
10 May 2018
Deep Directional Statistics: Pose Estimation with Uncertainty
  Quantification
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification
Sergey Prokudin
Peter V. Gehler
Sebastian Nowozin
UQCVOOD
153
98
0
09 May 2018
Improve Uncertainty Estimation for Unknown Classes in Bayesian Neural Networks with Semi-Supervised /One Set Classification
Buu Phan
UQCVBDL
149
0
0
04 May 2018
On the iterative refinement of densely connected representation levels
  for semantic segmentation
On the iterative refinement of densely connected representation levels for semantic segmentation
Arantxa Casanova
Guillem Cucurull
M. Drozdzal
Adriana Romero
Yoshua Bengio
SSeg
225
25
0
30 Apr 2018
Sampling-free Uncertainty Estimation in Gated Recurrent Units with
  Exponential Families
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families
Seong Jae Hwang
Ronak R. Mehta
Hyunwoo J. Kim
Vikas Singh
BDLUQCV
151
3
0
19 Apr 2018
The Limits and Potentials of Deep Learning for Robotics
The Limits and Potentials of Deep Learning for Robotics
Niko Sünderhauf
Oliver Brock
Walter J. Scheirer
R. Hadsell
Dieter Fox
...
B. Upcroft
Pieter Abbeel
Wolfram Burgard
Michael Milford
Peter Corke
244
547
0
18 Apr 2018
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural
  Network For Lidar 3D Vehicle Detection
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection
Di Feng
Lars Rosenbaum
Klaus C. J. Dietmayer
3DPCUQCV
266
265
0
13 Apr 2018
Improving Confidence Estimates for Unfamiliar Examples
Improving Confidence Estimates for Unfamiliar Examples
Zhizhong Li
Derek Hoiem
246
11
0
09 Apr 2018
Self-supervised Learning of Geometrically Stable Features Through
  Probabilistic Introspection
Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection
David Novotny
Samuel Albanie
Diane Larlus
Andrea Vedaldi
SSL
199
71
0
04 Apr 2018
Training VAEs Under Structured Residuals
Training VAEs Under Structured Residuals
Garoe Dorta
Sara Vicente
Lourdes Agapito
Neill D. F. Campbell
Ivor J. A. Simpson
BDLDRL
144
13
0
03 Apr 2018
CodeSLAM - Learning a Compact, Optimisable Representation for Dense
  Visual SLAM
CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM
Michael Bloesch
J. Czarnowski
R. Clark
Stefan Leutenegger
Andrew J. Davison
MDE3DH
247
411
0
03 Apr 2018
Safe end-to-end imitation learning for model predictive control
Safe end-to-end imitation learning for model predictive control
Keuntaek Lee
Kamil Saigol
Evangelos A. Theodorou
BDL
221
27
0
27 Mar 2018
Calibrated Prediction Intervals for Neural Network Regressors
Calibrated Prediction Intervals for Neural Network Regressors
Gil Keren
N. Cummins
Björn Schuller
UQCV
296
31
0
26 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick McDaniel
OODAAML
353
551
0
13 Mar 2018
Using Deep Learning for Segmentation and Counting within Microscopy Data
Using Deep Learning for Segmentation and Counting within Microscopy Data
Carlos X. Hernández
Mohammad M. Sultan
Vijay S. Pande
110
36
0
28 Feb 2018
Predictive Uncertainty Estimation via Prior Networks
Predictive Uncertainty Estimation via Prior NetworksNeural Information Processing Systems (NeurIPS), 2018
A. Malinin
Mark Gales
UDBDLEDLUQCVPER
651
1,034
0
28 Feb 2018
Active Learning with Partial Feedback
Active Learning with Partial Feedback
Peiyun Hu
Zachary Chase Lipton
Anima Anandkumar
Deva Ramanan
194
67
0
21 Feb 2018
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Eddy Ilg
Özgün Çiçek
Silvio Galesso
Aaron Klein
Osama Makansi
Katharina Eggensperger
Thomas Brox
UQCV
273
246
0
20 Feb 2018
Structured Uncertainty Prediction Networks
Structured Uncertainty Prediction Networks
Garoe Dorta
Sara Vicente
Lourdes Agapito
Neill D. F. Campbell
Ivor J. A. Simpson
UQCV
203
69
0
20 Feb 2018
Learning Confidence for Out-of-Distribution Detection in Neural Networks
Learning Confidence for Out-of-Distribution Detection in Neural Networks
Terrance Devries
Graham W. Taylor
OODOODD
274
632
0
13 Feb 2018
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