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2311.15816
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Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale
27 November 2023
Soyed Tuhin Ahmed
K. Danouchi
Michael Hefenbrock
G. Prenat
L. Anghel
M. Tahoori
UQCV
BDL
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Papers citing
"Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale"
10 / 10 papers shown
Title
Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights
Soyed Tuhin Ahmed
Michael Hefenbrock
M. Tahoori
UQCV
31
1
0
07 May 2024
Enhancing Fairness and Performance in Machine Learning Models: A Multi-Task Learning Approach with Monte-Carlo Dropout and Pareto Optimality
Khadija Zanna
Akane Sano
FaML
49
1
0
12 Apr 2024
Scalable and Efficient Methods for Uncertainty Estimation and Reduction in Deep Learning
Soyed Tuhin Ahmed
BDL
32
0
0
13 Jan 2024
NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI
Soyed Tuhin Ahmed
K. Danouchi
G. Prenat
L. Anghel
M. Tahoori
33
0
0
11 Jan 2024
Testing Spintronics Implemented Monte Carlo Dropout-Based Bayesian Neural Networks
Soyed Tuhin Ahmed
Michael Hefenbrock
G. Prenat
L. Anghel
M. Tahoori
24
0
0
09 Jan 2024
Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation
Soyed Tuhin Ahmed
K. Danouchi
Michael Hefenbrock
G. Prenat
L. Anghel
M. Tahoori
46
8
0
16 Jun 2023
Forward and Backward Information Retention for Accurate Binary Neural Networks
Haotong Qin
Ruihao Gong
Xianglong Liu
Mingzhu Shen
Ziran Wei
F. Yu
Jingkuan Song
MQ
133
324
0
24 Sep 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,675
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
336
75,888
0
18 May 2015
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