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Deeper Connections between Neural Networks and Gaussian Processes
  Speed-up Active Learning

Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning

27 February 2019
Evgenii Tsymbalov
Sergei Makarychev
Alexander Shapeev
Maxim Panov
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning"

5 / 5 papers shown
Title
Scalable Batch Acquisition for Deep Bayesian Active Learning
Scalable Batch Acquisition for Deep Bayesian Active Learning
Aleksandr Rubashevskii
Daria A. Kotova
Maxim Panov
BDL
27
3
0
13 Jan 2023
The Neural Process Family: Survey, Applications and Perspectives
The Neural Process Family: Survey, Applications and Perspectives
Saurav Jha
Dong Gong
Xuesong Wang
Richard Turner
L. Yao
BDL
83
24
0
01 Sep 2022
Accelerating high-throughput virtual screening through molecular
  pool-based active learning
Accelerating high-throughput virtual screening through molecular pool-based active learning
David E. Graff
E. Shakhnovich
Connor W. Coley
87
143
0
13 Dec 2020
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity
  as a Surrogate
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate
Lu Mi
Hao Wang
Yonglong Tian
Hao He
Nir Shavit
UQCV
23
30
0
28 Sep 2019
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
9,167
0
06 Jun 2015
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