Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale

27 November 2023

Papers citing "Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale"

5 / 5 papers shown

Title
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 41 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 128 324 0 24 Sep 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 273 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 294 75,800 0 18 May 2015