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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
Concept-Oriented Deep Learning: Generative Concept Representations
Concept-Oriented Deep Learning: Generative Concept Representations
Daniel T. Chang
DRLGANBDL
132
12
0
15 Nov 2018
Langevin-gradient parallel tempering for Bayesian neural learning
Langevin-gradient parallel tempering for Bayesian neural learning
Rohitash Chandra
Konark Jain
R. Deo
Sally Cripps
BDL
125
47
0
11 Nov 2018
A Bayesian Perspective of Statistical Machine Learning for Big Data
A Bayesian Perspective of Statistical Machine Learning for Big DataComputational statistics (Zeitschrift) (Comput. Stat.), 2018
R. Sambasivan
Sourish Das
S. Sahu
BDLGP
183
21
0
09 Nov 2018
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles
Kashyap Chitta
J. Álvarez
Adam Lesnikowski
BDLUQCV
257
37
0
08 Nov 2018
Deep Probabilistic Ensembles: Approximate Variational Inference through
  KL Regularization
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization
Matthew Maciejewski
J. Álvarez
Adam Lesnikowski
BDLUQCV
116
3
0
06 Nov 2018
Large-scale Heteroscedastic Regression via Gaussian Process
Large-scale Heteroscedastic Regression via Gaussian Process
Haitao Liu
Yew-Soon Ong
Jianfei Cai
BDL
294
30
0
03 Nov 2018
Single-Model Uncertainties for Deep Learning
Single-Model Uncertainties for Deep Learning
Natasa Tagasovska
David Lopez-Paz
UQCVBDL
581
26
0
02 Nov 2018
Safe Reinforcement Learning with Model Uncertainty Estimates
Safe Reinforcement Learning with Model Uncertainty Estimates
Björn Lütjens
Michael Everett
Jonathan P. How
231
187
0
19 Oct 2018
Probably Unknown: Deep Inverse Sensor Modelling In Radar
Probably Unknown: Deep Inverse Sensor Modelling In Radar
Rob Weston
Sarah H. Cen
Paul Newman
Ingmar Posner
156
83
0
18 Oct 2018
Good Initializations of Variational Bayes for Deep Models
Good Initializations of Variational Bayes for Deep Models
Simone Rossi
Pietro Michiardi
Maurizio Filippone
BDL
306
23
0
18 Oct 2018
Automatic Brain Tumor Segmentation using Convolutional Neural Networks
  with Test-Time Augmentation
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation
Guotai Wang
Wenqi Li
Sebastien Ourselin
Tom Vercauteren
113
166
0
18 Oct 2018
Embedded deep learning in ophthalmology: Making ophthalmic imaging
  smarter
Embedded deep learning in ophthalmology: Making ophthalmic imaging smarter
Petteri Teikari
Raymond P. Najjar
L. Schmetterer
D. Milea
MedIm
239
31
0
13 Oct 2018
Functionally Modular and Interpretable Temporal Filtering for Robust
  Segmentation
Functionally Modular and Interpretable Temporal Filtering for Robust Segmentation
Jörg Wagner
Volker Fischer
Michael Herman
Sven Behnke
183
1
0
09 Oct 2018
Hierarchical Recurrent Filtering for Fully Convolutional DenseNets
Hierarchical Recurrent Filtering for Fully Convolutional DenseNets
Jörg Wagner
Volker Fischer
Michael Herman
Sven Behnke
130
1
0
05 Oct 2018
PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation
PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation
Perttu Hämäläinen
Amin Babadi
Xiaoxiao Ma
J. Lehtinen
418
67
0
05 Oct 2018
Inhibited Softmax for Uncertainty Estimation in Neural Networks
Inhibited Softmax for Uncertainty Estimation in Neural Networks
Marcin Mo.zejko
Mateusz Susik
Rafal Karczewski
UQCV
161
35
0
03 Oct 2018
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods
Apratim Bhattacharyya
Mario Fritz
Bernt Schiele
UQCV
305
47
0
01 Oct 2018
Modeling Uncertainty with Hedged Instance Embedding
Modeling Uncertainty with Hedged Instance Embedding
Seong Joon Oh
Kevin Patrick Murphy
Jiyan Pan
Joseph Roth
Florian Schroff
Andrew C. Gallagher
UQCV
1.2K
83
0
30 Sep 2018
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation
  Learning
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation LearningJournal of machine learning research (JMLR), 2018
Daniel Coelho De Castro
Jeremy Tan
Bernhard Kainz
E. Konukoglu
Ben Glocker
DRL
268
86
0
27 Sep 2018
Dropout Distillation for Efficiently Estimating Model Confidence
Dropout Distillation for Efficiently Estimating Model Confidence
Corina Gurau
Alex Bewley
Ingmar Posner
BDLUQCV
102
22
0
27 Sep 2018
Diagnostics in Semantic Segmentation
Diagnostics in Semantic Segmentation
Vladimir Nekrasov
Chunhua Shen
Ian Reid
VLMSSeg
105
3
0
27 Sep 2018
Left Ventricle Segmentation and Quantification from Cardiac Cine MR
  Images via Multi-task Learning
Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning
Shusil Dangi
Z. Yaniv
Cristian A. Linte
174
24
0
26 Sep 2018
Confidence Inference for Focused Learning in Stereo Matching
Confidence Inference for Focused Learning in Stereo Matching
Ruichao Xiao
Wenxiu Sun
Chengxi Yang
BDL3DV
76
2
0
25 Sep 2018
Bounding Box Regression with Uncertainty for Accurate Object Detection
Bounding Box Regression with Uncertainty for Accurate Object Detection
Yihui He
Chenchen Zhu
Jianren Wang
Marios Savvides
Xinming Zhang
ObjD
273
517
0
23 Sep 2018
Quantifying total uncertainty in physics-informed neural networks for
  solving forward and inverse stochastic problems
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Dongkun Zhang
Lu Lu
Ling Guo
George Karniadakis
UQCV
308
483
0
21 Sep 2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques
  in Object Detection
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection
Dimity Miller
Feras Dayoub
Michael Milford
Niko Sünderhauf
264
113
0
17 Sep 2018
Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time
  LiDAR 3D Object Detection
Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection
Di Feng
Lars Rosenbaum
Fabian Timm
Klaus C. J. Dietmayer
3DPC
232
72
0
14 Sep 2018
Deep Network Uncertainty Maps for Indoor Navigation
Deep Network Uncertainty Maps for Indoor Navigation
Francesco Verdoja
Jens Lundell
Ville Kyrki
UQCV
163
24
0
13 Sep 2018
Real-Time Joint Semantic Segmentation and Depth Estimation Using
  Asymmetric Annotations
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Vladimir Nekrasov
Thanuja Dharmasiri
Andrew Spek
Tom Drummond
Chunhua Shen
Ian Reid
261
155
0
13 Sep 2018
A Less Biased Evaluation of Out-of-distribution Sample Detectors
A Less Biased Evaluation of Out-of-distribution Sample Detectors
Alireza Shafaei
Mark Schmidt
James J. Little
OODD
261
59
0
13 Sep 2018
Joint Segmentation and Uncertainty Visualization of Retinal Layers in
  Optical Coherence Tomography Images using Bayesian Deep Learning
Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning
S. Sedai
B. Antony
Dwarikanath Mahapatra
R. Garnavi
UQCV
135
65
0
12 Sep 2018
Deep Depth from Defocus: how can defocus blur improve 3D estimation
  using dense neural networks?
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?
Marcela Carvalho
Bertrand Le Saux
Pauline Trouvé-Peloux
Andrés Almansa
F. Champagnat
3DVMDE
154
60
0
05 Sep 2018
Discriminative out-of-distribution detection for semantic segmentation
Discriminative out-of-distribution detection for semantic segmentation
Petra Bevandić
Ivan Kreso
Marin Orsic
Sinisa Segvic
211
86
0
23 Aug 2018
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for
  Autonomous Driving
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
Nemanja Djuric
Vladan Radosavljevic
Henggang Cui
Thi Nguyen
Fang-Chieh Chou
Tsung-Han Lin
Nitin Singh
J. Schneider
264
221
0
17 Aug 2018
Deep Bayesian Active Learning for Natural Language Processing: Results
  of a Large-Scale Empirical Study
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study
Aditya Siddhant
Zachary Chase Lipton
AI4CEBDL
283
219
0
16 Aug 2018
Analyzing Inverse Problems with Invertible Neural Networks
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone
Jakob Kruse
Sebastian J. Wirkert
D. Rahner
E. Pellegrini
R. Klessen
Lena Maier-Hein
Carsten Rother
Ullrich Kothe
369
546
0
14 Aug 2018
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis
  Lesion Detection and Segmentation
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation
T. Nair
Doina Precup
Douglas L. Arnold
Tal Arbel
UQCV
247
478
0
03 Aug 2018
Scalable Multi-Task Gaussian Process Tensor Regression for Normative
  Modeling of Structured Variation in Neuroimaging Data
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data
S. M. Kia
Christian F. Beckmann
A. Marquand
189
7
0
31 Jul 2018
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape
  Priors
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors
Katarína Tóthová
Sarah Parisot
M. J. Lee
Esther Puyol-Antón
Lisa M. Koch
A. King
E. Konukoglu
Marc Pollefeys
UQCV
105
21
0
30 Jul 2018
Efficient Uncertainty Estimation for Semantic Segmentation in Videos
Efficient Uncertainty Estimation for Semantic Segmentation in Videos
Po-Yu Huang
W. Hsu
Chun-Yueh Chiu
Tingfan Wu
Min Sun
BDLUQCV
140
114
0
29 Jul 2018
Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy
  Series
Uncertainty Modelling in Deep Networks: Forecasting Short and Noisy Series
Axel Brando
Jose A. Rodríguez-Serrano
M. Ciprian
Roberto Maestre
Jordi Vitrià
98
18
0
24 Jul 2018
Peeking Behind Objects: Layered Depth Prediction from a Single Image
Peeking Behind Objects: Layered Depth Prediction from a Single Image
Helisa Dhamo
Keisuke Tateno
Iro Laina
Nassir Navab
Federico Tombari
GAN3DV
186
64
0
23 Jul 2018
Aleatoric uncertainty estimation with test-time augmentation for medical
  image segmentation with convolutional neural networks
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Guotai Wang
Wenqi Li
Michael Aertsen
Jan Deprest
Sebastien Ourselin
Tom Vercauteren
UQCVMedImOOD
328
656
0
19 Jul 2018
A Dataset of Laryngeal Endoscopic Images with Comparative Study on
  Convolution Neural Network Based Semantic Segmentation
A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic SegmentationInternational Journal of Computer Assisted Radiology and Surgery (IJCARS), 2018
M. Laves
J. Bicker
L. Kahrs
T. Ortmaier
238
101
0
16 Jul 2018
Uncertainty and Interpretability in Convolutional Neural Networks for
  Semantic Segmentation of Colorectal Polyps
Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal PolypsInternational Workshop on Machine Learning for Signal Processing (MLSP), 2018
Kristoffer Wickstrøm
Michael C. Kampffmeyer
Robert Jenssen
UQCV
152
77
0
16 Jul 2018
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation
  using CNNs
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Thanuja Dharmasiri
Andrew Spek
Tom Drummond
3DVMDE
177
17
0
16 Jul 2018
Adversarially Learned Mixture Model
Adversarially Learned Mixture Model
Andrew Jesson
Cécile Low-Kam
Tanya Nair
F. Soudan
Florent Chandelier
Nicolas Chapados
131
2
0
14 Jul 2018
Practical Obstacles to Deploying Active Learning
Practical Obstacles to Deploying Active Learning
David Lowell
Zachary Chase Lipton
Byron C. Wallace
302
118
0
12 Jul 2018
VFunc: a Deep Generative Model for Functions
VFunc: a Deep Generative Model for Functions
Philip Bachman
Riashat Islam
Alessandro Sordoni
Zafarali Ahmed
VLMBDL
139
8
0
11 Jul 2018
Adaptive Adversarial Attack on Scene Text Recognition
Adaptive Adversarial Attack on Scene Text RecognitionConference on Computer Communications Workshops (INFOCOM), 2018
Xiaoyong Yuan
Pan He
Xiaolin Li
Dapeng Oliver Wu
AAML
170
25
0
09 Jul 2018
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