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UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC
  Diabetic Retinopathy Detection
v1v2 (latest)

UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection

6 November 2022
Pratinav Seth
Adil Mehmood Khan
Ananya Gupta
Saurabh Mishra
Akshat Bhandhari
ArXiv (abs)PDFHTML

Papers citing "UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection"

9 / 9 papers shown
Title
Uncertainty-aware deep learning methods for robust diabetic retinopathy
  classification
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification
J. Jaskari
J. Sahlsten
Theodoros Damoulas
Jeremias Knoblauch
Simo Särkkä
L. Kärkkäinen
K. Hietala
K. Kaski
BDLUQCV
44
28
0
22 Jan 2022
Evaluating Predictive Uncertainty and Robustness to Distributional Shift
  Using Real World Data
Evaluating Predictive Uncertainty and Robustness to Distributional Shift Using Real World Data
Kumud Lakara
Akshat Bhandari
Pratinav Seth
Ujjwal Verma
OOD
57
4
0
08 Nov 2021
Uncertainty Quantification and Deep Ensembles
Uncertainty Quantification and Deep Ensembles
R. Rahaman
Alexandre Hoang Thiery
UQCV
83
154
0
17 Jul 2020
Calibration tests in multi-class classification: A unifying framework
Calibration tests in multi-class classification: A unifying framework
David Widmann
Fredrik Lindsten
Dave Zachariah
78
94
0
24 Oct 2019
Deep Neural Networks as Gaussian Processes
Deep Neural Networks as Gaussian Processes
Jaehoon Lee
Yasaman Bahri
Roman Novak
S. Schoenholz
Jeffrey Pennington
Jascha Narain Sohl-Dickstein
UQCVBDL
131
1,097
0
01 Nov 2017
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry
  and Semantics
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
Alex Kendall
Y. Gal
R. Cipolla
3DH
272
3,123
0
19 May 2017
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
226
1,518
0
08 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
UQCVBDL
831
9,345
0
06 Jun 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural
  Networks
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
José Miguel Hernández-Lobato
Ryan P. Adams
UQCVBDL
130
946
0
18 Feb 2015
1