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Nonparametric Uncertainty Quantification for Single Deterministic Neural
  Network

Nonparametric Uncertainty Quantification for Single Deterministic Neural Network

7 February 2022
Nikita Kotelevskii
A. Artemenkov
Kirill Fedyanin
Fedor Noskov
Alexander Fishkov
Artem Shelmanov
Artem Vazhentsev
Aleksandr Petiushko
Maxim Panov
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Nonparametric Uncertainty Quantification for Single Deterministic Neural Network"

6 / 6 papers shown
Title
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Wataru Hashimoto
Hidetaka Kamigaito
Taro Watanabe
57
0
0
02 Jul 2024
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin
Ekaterina Fadeeva
Artem Vazhentsev
Akim Tsvigun
Daniil Vasilev
...
Timothy Baldwin
Timothy Baldwin
Maxim Panov
Artem Shelmanov
Artem Shelmanov
HILM
66
8
0
21 Jun 2024
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiers
Johann Schmidt
Sebastian Stober
43
1
0
06 May 2024
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
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
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
1