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Out of Distribution Data Detection Using Dropout Bayesian Neural
  Networks

Out of Distribution Data Detection Using Dropout Bayesian Neural Networks

AAAI Conference on Artificial Intelligence (AAAI), 2022
18 February 2022
A. Nguyen
Fred Lu
Gary Lopez Munoz
Edward Raff
Charles K. Nicholas
James Holt
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Out of Distribution Data Detection Using Dropout Bayesian Neural Networks"

11 / 11 papers shown
Out-of-Distribution Detection from Small Training Sets using Bayesian Neural Network Classifiers
Out-of-Distribution Detection from Small Training Sets using Bayesian Neural Network Classifiers
Kevin Raina
T. Schmah
BDL
156
0
0
07 Oct 2025
Logit Disagreement: OoD Detection with Bayesian Neural Networks
Logit Disagreement: OoD Detection with Bayesian Neural Networks
Kevin Raina
UQCVBDLUDPER
424
1
0
24 Feb 2025
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
On the Privacy Risks of Spiking Neural Networks: A Membership Inference AnalysisConference on Uncertainty in Artificial Intelligence (UAI), 2025
Junyi Guan
Abhijith Sharma
Chong Tian
Salem Lahlou
AAML
427
2
0
18 Feb 2025
Living off the Analyst: Harvesting Features from Yara Rules for Malware
  Detection
Living off the Analyst: Harvesting Features from Yara Rules for Malware DetectionBigData Congress [Services Society] (BSS), 2024
Siddhant Gupta
Fred Lu
Andrew Barlow
Edward Raff
Francis Ferraro
Cynthia Matuszek
Charles K. Nicholas
James Holt
308
1
0
27 Nov 2024
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou
Hai-Miao Hu
Yirong Xiang
Xiaokang Zhang
Haotian Wu
230
11
0
08 May 2024
Focused Active Learning for Histopathological Image Classification
Focused Active Learning for Histopathological Image Classification
Arne Schmidt
Pablo Morales-Álvarez
Lee A.D. Cooper
L. Newberg
A. Enquobahrie
Aggelos K. Katsaggelos
Rafael Molina
204
10
0
06 Apr 2024
Learning with Mixture of Prototypes for Out-of-Distribution Detection
Learning with Mixture of Prototypes for Out-of-Distribution Detection
Haodong Lu
Dong Gong
Shuo Wang
Jason Xue
Lina Yao
Kristen Moore
OODD
283
45
0
05 Feb 2024
Can input reconstruction be used to directly estimate uncertainty of a
  regression U-Net model? -- Application to proton therapy dose prediction for
  head and neck cancer patients
Can input reconstruction be used to directly estimate uncertainty of a regression U-Net model? -- Application to proton therapy dose prediction for head and neck cancer patients
Margerie Huet-Dastarac
Dan Nguyen
Steve B. Jiang
John A. Lee
A. M. Barragán-Montero
OODUQCV
150
0
0
30 Oct 2023
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via
  Bayesian Uncertainty Alignment
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty AlignmentIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Kecheng Chen
Jie Liu
Renjie Wan
Victor Ho-Fun Lee
Varut Vardhanabhuti
Hong Yan
Haoliang Li
OOD
299
7
0
26 Feb 2023
Improving Out-of-Distribution Detection via Epistemic Uncertainty
  Adversarial Training
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training
Derek Everett
A. Nguyen
Luke E. Richards
Edward Raff
OODD
168
4
0
05 Sep 2022
Simple and Principled Uncertainty Estimation with Deterministic Deep
  Learning via Distance Awareness
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCVBDL
831
518
0
17 Jun 2020
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