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Adapting Neural Models with Sequential Monte Carlo Dropout

Adapting Neural Models with Sequential Monte Carlo Dropout

27 October 2022
Pamela Carreno-Medrano
Dana Kulić
Michael G. Burke
ArXivPDFHTML

Papers citing "Adapting Neural Models with Sequential Monte Carlo Dropout"

3 / 3 papers shown
Title
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
228
498
0
11 Jun 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
446
11,715
0
09 Mar 2017
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
UQCV
BDL
287
9,156
0
06 Jun 2015
1