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Can You Trust Your Model's Uncertainty? Evaluating Predictive
  Uncertainty Under Dataset Shift
v1v2 (latest)

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

6 June 2019
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift"

50 / 1,062 papers shown
Title
Locally Sparse Neural Networks for Tabular Biomedical Data
Locally Sparse Neural Networks for Tabular Biomedical Data
Junchen Yang
Ofir Lindenbaum
Y. Kluger
87
34
0
11 Jun 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under
  Varying Testing Environments?
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng
Stephen Gould
Liang Zheng
103
64
0
10 Jun 2021
Understanding the Under-Coverage Bias in Uncertainty Estimation
Understanding the Under-Coverage Bias in Uncertainty Estimation
Yu Bai
Song Mei
Huan Wang
Caiming Xiong
UQCV
56
13
0
10 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and Primer
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zhangyang Wang
J. Yadawa
91
32
0
09 Jun 2021
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain
  Adaptation
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
David Berthelot
Rebecca Roelofs
Kihyuk Sohn
Nicholas Carlini
Alexey Kurakin
61
145
0
08 Jun 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep
  Learning
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
Zachary Nado
Neil Band
Mark Collier
Josip Djolonga
Michael W. Dusenberry
...
D. Sculley
Balaji Lakshminarayanan
Jasper Snoek
Y. Gal
Dustin Tran
UQCVELM
130
96
0
07 Jun 2021
Shifting Transformation Learning for Out-of-Distribution Detection
Shifting Transformation Learning for Out-of-Distribution Detection
Sina Mohseni
Arash Vahdat
J. Yadawa
OODD
58
9
0
07 Jun 2021
Counterfactual Maximum Likelihood Estimation for Training Deep Networks
Counterfactual Maximum Likelihood Estimation for Training Deep Networks
Xinyi Wang
Wenhu Chen
Michael Stephen Saxon
Wenjie Wang
OODCMLBDL
107
8
0
07 Jun 2021
Frustratingly Easy Uncertainty Estimation for Distribution Shift
Frustratingly Easy Uncertainty Estimation for Distribution Shift
Tiago Salvador
Vikram S. Voleti
Alexander Iannantuono
Adam M. Oberman
OODUQCV
70
1
0
07 Jun 2021
Can a single neuron learn predictive uncertainty?
Can a single neuron learn predictive uncertainty?
Edgardo Solano-Carrillo
UQCV
74
1
0
07 Jun 2021
Evidential Turing Processes
Evidential Turing Processes
M. Kandemir
Abdullah Akgul
Manuel Haussmann
Gözde B. Ünal
EDLUQCVBDL
70
10
0
02 Jun 2021
Uncertainty Characteristics Curves: A Systematic Assessment of
  Prediction Intervals
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals
Jirí Navrátil
Benjamin Elder
Matthew Arnold
S. Ghosh
P. Sattigeri
34
5
0
01 Jun 2021
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated
  learning
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
Maxime Vono
Vincent Plassier
Alain Durmus
Hadrien Hendrikx
Eric Moulines
FedML
93
36
0
01 Jun 2021
Closer Look at the Uncertainty Estimation in Semantic Segmentation under
  Distributional Shift
Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
Sebastian Cygert
Bartlomiej Wróblewski
Karol Wozniak
Radoslaw Slowiñski
A. Czyżewski
UQCVOOD
65
7
0
31 May 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights
Sparse Uncertainty Representation in Deep Learning with Inducing Weights
H. Ritter
Martin Kukla
Chen Zhang
Yingzhen Li
UQCVBDL
90
17
0
30 May 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles
Greedy Bayesian Posterior Approximation with Deep Ensembles
A. Tiulpin
Matthew B. Blaschko
UQCVFedML
91
4
0
29 May 2021
Learning Uncertainty For Safety-Oriented Semantic Segmentation In
  Autonomous Driving
Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving
Victor Besnier
David Picard
Alexandre Briot
UQCV
55
11
0
28 May 2021
Deep Ensembles from a Bayesian Perspective
Deep Ensembles from a Bayesian Perspective
L. Hoffmann
Clemens Elster
UDBDLUQCV
74
38
0
27 May 2021
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy,
  Uncertainty, and Robustness
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness
Namuk Park
S. Kim
UQCVAAML
93
21
0
26 May 2021
DeepGaze IIE: Calibrated prediction in and out-of-domain for
  state-of-the-art saliency modeling
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling
Akis Linardos
Matthias Kümmerer
Ori Press
Matthias Bethge
MDE
72
66
0
26 May 2021
Mapping oil palm density at country scale: An active learning approach
Mapping oil palm density at country scale: An active learning approach
Andrés C. Rodríguez
Stefano Dáronco
Konrad Schindler
Jan Dirk Wegner
91
41
0
24 May 2021
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Agostina J. Larrazabal
Cesar E. Martínez
Jose Dolz
Enzo Ferrante
UQCV
75
22
0
22 May 2021
Correlated Input-Dependent Label Noise in Large-Scale Image
  Classification
Correlated Input-Dependent Label Noise in Large-Scale Image Classification
Mark Collier
Basil Mustafa
Efi Kokiopoulou
Rodolphe Jenatton
Jesse Berent
NoLa
236
54
0
19 May 2021
Scaling Ensemble Distribution Distillation to Many Classes with Proxy
  Targets
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets
Max Ryabinin
A. Malinin
Mark Gales
UQCV
53
18
0
14 May 2021
BNNpriors: A library for Bayesian neural network inference with
  different prior distributions
BNNpriors: A library for Bayesian neural network inference with different prior distributions
Vincent Fortuin
Adrià Garriga-Alonso
Mark van der Wilk
Laurence Aitchison
BDLUQCV
93
25
0
14 May 2021
Priors in Bayesian Deep Learning: A Review
Priors in Bayesian Deep Learning: A Review
Vincent Fortuin
UQCVBDL
137
134
0
14 May 2021
Stochastic-Shield: A Probabilistic Approach Towards Training-Free
  Adversarial Defense in Quantized CNNs
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs
Lorena Qendro
Sangwon Ha
R. D. Jong
Partha P. Maji
AAMLFedMLMQ
58
7
0
13 May 2021
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
Vincent Dutordoir
J. Hensman
Mark van der Wilk
Carl Henrik Ek
Zoubin Ghahramani
N. Durrande
BDLUQCV
106
31
0
10 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential
  Family Distributions
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
Bertrand Charpentier
Oliver Borchert
Daniel Zügner
Simon Geisler
Stephan Günnemann
UQCVBDL
70
17
0
10 May 2021
Topological Uncertainty: Monitoring trained neural networks through
  persistence of activation graphs
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs
Théo Lacombe
Yuichi Ike
Mathieu Carrière
Frédéric Chazal
Marc Glisse
Yuhei Umeda
75
23
0
07 May 2021
Structured Ensembles: an Approach to Reduce the Memory Footprint of
  Ensemble Methods
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble Methods
Jary Pomponi
Simone Scardapane
A. Uncini
UQCV
58
7
0
06 May 2021
What Are Bayesian Neural Network Posteriors Really Like?
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov
Sharad Vikram
Matthew D. Hoffman
A. Wilson
UQCVBDL
81
389
0
29 Apr 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI
  Safety
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben
Stephanie Abrecht
Maram Akila
Andreas Bär
Felix Brockherde
...
Serin Varghese
Michael Weber
Sebastian J. Wirkert
Tim Wirtz
Matthias Woehrle
AAML
126
58
0
29 Apr 2021
Deep Learning for Bayesian Optimization of Scientific Problems with
  High-Dimensional Structure
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure
Samuel Kim
Peter Y. Lu
Charlotte Loh
Jamie Smith
Jasper Snoek
M. Soljavcić
BDLAI4CE
389
17
0
23 Apr 2021
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings
U. Sarawgi
Rishab Khincha
W. Zulfikar
Satrajit S. Ghosh
Pattie Maes
UQCV
55
7
0
21 Apr 2021
On the Importance of Effectively Adapting Pretrained Language Models for
  Active Learning
On the Importance of Effectively Adapting Pretrained Language Models for Active Learning
Katerina Margatina
Loïc Barrault
Nikolaos Aletras
85
39
0
16 Apr 2021
I Find Your Lack of Uncertainty in Computer Vision Disturbing
I Find Your Lack of Uncertainty in Computer Vision Disturbing
Matias Valdenegro-Toro
UQCV
53
21
0
16 Apr 2021
Multivariate Deep Evidential Regression
Multivariate Deep Evidential Regression
N. Meinert
Alexander Lavin
BDLPEREDLUQCV
85
21
0
13 Apr 2021
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting
  the Long-Tail of Unseen Conditions
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
Abhijit Guha Roy
Jie Jessie Ren
Shekoofeh Azizi
Aaron Loh
Vivek Natarajan
...
Yun-Hui Liu
taylan. cemgil
Alan Karthikesalingam
Balaji Lakshminarayanan
Jim Winkens
117
109
0
08 Apr 2021
Out-of-Distribution Robustness with Deep Recursive Filters
Out-of-Distribution Robustness with Deep Recursive Filters
Kapil D. Katyal
I-J. Wang
Gregory D. Hager
UQCV
29
0
0
06 Apr 2021
Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data
Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data
Tong Xia
Jing Han
Lorena Qendro
T. Dang
Cecilia Mascolo
90
28
0
05 Apr 2021
Diverse Gaussian Noise Consistency Regularization for Robustness and
  Uncertainty Calibration
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration
Theodoros Tsiligkaridis
Athanasios Tsiligkaridis
98
3
0
02 Apr 2021
Elsa: Energy-based learning for semi-supervised anomaly detection
Elsa: Energy-based learning for semi-supervised anomaly detection
Sungwon Han
Hyeonho Song
Seungeon Lee
Sungwon Park
M. Cha
83
12
0
29 Mar 2021
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Bayesian Deep Basis Fitting for Depth Completion with Uncertainty
Chao Qu
Wenxin Liu
Camillo J Taylor
UQCVBDL
88
31
0
29 Mar 2021
Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems
Adaptive Autonomy in Human-on-the-Loop Vision-Based Robotics Systems
Sophia J. Abraham
Zachariah Carmichael
Sreya Banerjee
Rosaura G. VidalMata
Ankit Agrawal
M. N. A. Islam
Walter J. Scheirer
J. Cleland-Huang
66
20
0
28 Mar 2021
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware
  Regression
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
Wanhua Li
Xiaoke Huang
Jiwen Lu
Jianjiang Feng
Jie Zhou
UQCV
149
65
0
25 Mar 2021
Automated and Autonomous Experiment in Electron and Scanning Probe
  Microscopy
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy
Sergei V. Kalinin
M. Ziatdinov
Jacob D. Hinkle
S. Jesse
Ayana Ghosh
K. Kelley
A. Lupini
B. Sumpter
Rama K Vasudevan
72
3
0
22 Mar 2021
Robustness via Cross-Domain Ensembles
Robustness via Cross-Domain Ensembles
Teresa Yeo
Oğuzhan Fatih Kar
Alexander Sax
Amir Zamir
UQCVOOD
57
25
0
19 Mar 2021
Decision Theoretic Bootstrapping
Decision Theoretic Bootstrapping
P. Tavallali
Hamed Hamze Bajgiran
Danial Esaid
H. Owhadi
47
0
0
18 Mar 2021
Learning Word-Level Confidence For Subword End-to-End ASR
Learning Word-Level Confidence For Subword End-to-End ASR
David Qiu
Qiujia Li
Yanzhang He
Yu Zhang
Yue Liu
...
Deepti Bhatia
Wei Li
Ke Hu
Tara N. Sainath
Ian McGraw
51
32
0
11 Mar 2021
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