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Building Bayesian Neural Networks with Blocks: On Structure,
  Interpretability and Uncertainty

Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty

10 June 2018
Hao Zhou
Yunyang Xiong
Vikas Singh
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty"

2 / 2 papers shown
Title
Locality defeats the curse of dimensionality in convolutional
  teacher-student scenarios
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios
Alessandro Favero
Francesco Cagnetta
M. Wyart
24
31
0
16 Jun 2021
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
285
9,136
0
06 Jun 2015
1