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Evaluating High-Order Predictive Distributions in Deep Learning

Evaluating High-Order Predictive Distributions in Deep Learning

28 February 2022
Ian Osband
Zheng Wen
S. Asghari
Vikranth Dwaracherla
Xiuyuan Lu
Benjamin Van Roy
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Papers citing "Evaluating High-Order Predictive Distributions in Deep Learning"

11 / 11 papers shown
Title
Making Better Use of Unlabelled Data in Bayesian Active Learning
Making Better Use of Unlabelled Data in Bayesian Active Learning
Freddie Bickford-Smith
Adam Foster
Tom Rainforth
36
3
0
26 Apr 2024
Efficient Exploration for LLMs
Efficient Exploration for LLMs
Vikranth Dwaracherla
S. Asghari
Botao Hao
Benjamin Van Roy
LLMAG
15
20
0
01 Feb 2024
Fine-Tuning Language Models via Epistemic Neural Networks
Fine-Tuning Language Models via Epistemic Neural Networks
Ian Osband
S. Asghari
Benjamin Van Roy
Nat McAleese
John Aslanides
G. Irving
UQLM
31
16
0
03 Nov 2022
Sampling-based inference for large linear models, with application to
  linearised Laplace
Sampling-based inference for large linear models, with application to linearised Laplace
Javier Antorán
Shreyas Padhy
Riccardo Barbano
Eric T. Nalisnick
David Janz
José Miguel Hernández-Lobato
BDL
27
17
0
10 Oct 2022
Robustness of Epinets against Distributional Shifts
Robustness of Epinets against Distributional Shifts
Xiuyuan Lu
Ian Osband
S. Asghari
Sven Gowal
Vikranth Dwaracherla
Zheng Wen
Benjamin Van Roy
UQCV
OOD
16
0
0
01 Jul 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and
  Bootstrapping
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping
Vikranth Dwaracherla
Zheng Wen
Ian Osband
Xiuyuan Lu
S. Asghari
Benjamin Van Roy
UQCV
24
17
0
08 Jun 2022
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian
  Inference, Active Learning, and Active Sampling
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling
Andreas Kirsch
Jannik Kossen
Y. Gal
UQCV
BDL
52
3
0
18 May 2022
The Neural Testbed: Evaluating Joint Predictions
The Neural Testbed: Evaluating Joint Predictions
Ian Osband
Zheng Wen
S. Asghari
Vikranth Dwaracherla
Botao Hao
M. Ibrahimi
Dieterich Lawson
Xiuyuan Lu
Brendan O'Donoghue
Benjamin Van Roy
UQCV
29
21
0
09 Oct 2021
Epistemic Neural Networks
Epistemic Neural Networks
Ian Osband
Zheng Wen
M. Asghari
Vikranth Dwaracherla
M. Ibrahimi
Xiyuan Lu
Benjamin Van Roy
UQCV
BDL
30
97
0
19 Jul 2021
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
276
5,661
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
9,138
0
06 Jun 2015
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