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Ensembles for Uncertainty Estimation: Benefits of Prior Functions and
  Bootstrapping

Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping

8 June 2022
Vikranth Dwaracherla
Zheng Wen
Ian Osband
Xiuyuan Lu
S. Asghari
Benjamin Van Roy
    UQCV
ArXivPDFHTML

Papers citing "Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping"

17 / 17 papers shown
Title
Trends, Challenges, and Future Directions in Deep Learning for Glaucoma:
  A Systematic Review
Trends, Challenges, and Future Directions in Deep Learning for Glaucoma: A Systematic Review
Mahtab Faraji
Homa Rashidisabet
George R. Nahass
R. Chan
Thasarat S Vajaranant
Darvin Yi
32
0
0
07 Nov 2024
Satisficing Exploration for Deep Reinforcement Learning
Satisficing Exploration for Deep Reinforcement Learning
Dilip Arumugam
Saurabh Kumar
Ramki Gummadi
Benjamin Van Roy
34
1
0
16 Jul 2024
Online Bandit Learning with Offline Preference Data for Improved RLHF
Online Bandit Learning with Offline Preference Data for Improved RLHF
Akhil Agnihotri
Rahul Jain
Deepak Ramachandran
Zheng Wen
OffRL
37
1
0
13 Jun 2024
To Believe or Not to Believe Your LLM
To Believe or Not to Believe Your LLM
Yasin Abbasi-Yadkori
Ilja Kuzborskij
András György
Csaba Szepesvári
UQCV
59
40
0
04 Jun 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
Oleksandr Balabanov
H. Linander
UQCV
28
13
0
19 Feb 2024
Probabilistic Inference in Reinforcement Learning Done Right
Probabilistic Inference in Reinforcement Learning Done Right
Jean Tarbouriech
Tor Lattimore
Brendan O'Donoghue
BDL
OffRL
20
4
0
22 Nov 2023
Using AI Uncertainty Quantification to Improve Human Decision-Making
Using AI Uncertainty Quantification to Improve Human Decision-Making
L. Marusich
J. Bakdash
Yan Zhou
Murat Kantarcioglu
16
3
0
19 Sep 2023
Likelihood-ratio-based confidence intervals for neural networks
Likelihood-ratio-based confidence intervals for neural networks
Laurens Sluijterman
Eric Cator
Tom Heskes
UQCV
27
0
0
04 Aug 2023
Bayesian Quadrature for Neural Ensemble Search
Bayesian Quadrature for Neural Ensemble Search
Saad Hamid
Xingchen Wan
Martin Jørgensen
Binxin Ru
Michael A. Osborne
BDL
UQCV
28
1
0
15 Mar 2023
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization
Brendan O'Donoghue
OffRL
27
6
0
18 Feb 2023
Leveraging Demonstrations to Improve Online Learning: Quality Matters
Leveraging Demonstrations to Improve Online Learning: Quality Matters
Botao Hao
Rahul Jain
Tor Lattimore
Benjamin Van Roy
Zheng Wen
16
8
0
07 Feb 2023
Bayesian posterior approximation with stochastic ensembles
Bayesian posterior approximation with stochastic ensembles
Oleksandr Balabanov
Bernhard Mehlig
H. Linander
BDL
UQCV
27
5
0
15 Dec 2022
Augmenting Neural Networks with Priors on Function Values
Augmenting Neural Networks with Priors on Function Values
Hunter Nisonoff
Yixin Wang
Jennifer Listgarten
23
3
0
10 Feb 2022
Epistemic Neural Networks
Epistemic Neural Networks
Ian Osband
Zheng Wen
M. Asghari
Vikranth Dwaracherla
M. Ibrahimi
Xiyuan Lu
Benjamin Van Roy
UQCV
BDL
25
97
0
19 Jul 2021
Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision
  Making
Stochastic Low-rank Tensor Bandits for Multi-dimensional Online Decision Making
Jie Zhou
Botao Hao
Zheng Wen
Jingfei Zhang
W. Sun
30
6
0
31 Jul 2020
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
279
9,136
0
06 Jun 2015
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