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2005.08414
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Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs
18 May 2020
T. Goda
Tomohiko Hironaka
Wataru Kitade
Adam Foster
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Papers citing
"Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs"
16 / 16 papers shown
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Approximation of differential entropy in Bayesian optimal experimental design
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Yuya Suzuki
148
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BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design
Deepro Choudhury
Sinead Williamson
Adam Goliñski
Ning Miao
Freddie Bickford-Smith
Michael Kirchhof
Yizhe Zhang
Tom Rainforth
271
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28 Aug 2025
Evasion Attacks Against Bayesian Predictive Models
Conference on Uncertainty in Artificial Intelligence (UAI), 2025
Pablo G. Arce
Roi Naveiro
D. Insua
AAML
307
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11 Jun 2025
Multilevel neural simulation-based inference
Yuga Hikida
Ayush Bharti
Niall Jeffrey
F. Briol
459
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06 Jun 2025
Bayesian Experimental Design via Contrastive Diffusions
International Conference on Learning Representations (ICLR), 2024
Jacopo Iollo
Christophe Heinkelé
Pierre Alliez
Florence Forbes
399
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15 Oct 2024
When are Unbiased Monte Carlo Estimators More Preferable than Biased Ones?
Guanyang Wang
Jose Blanchet
Peter Glynn
337
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01 Apr 2024
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang
Vitaly Zankin
Maximilian Balandat
Stefan Scherer
Kevin Carlberg
Neil S. Walton
Kody J. H. Law
397
4
0
03 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods
Xiliang Yang
Yifei Xiong
Zhijian He
558
0
0
30 Jan 2024
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design
AAAI Conference on Artificial Intelligence (AAAI), 2023
Ziqiao Ao
Jinglai Li
271
4
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19 Aug 2023
Modern Bayesian Experimental Design
Statistical Science (Statist. Sci.), 2023
Tom Rainforth
Adam Foster
Desi R. Ivanova
Freddie Bickford-Smith
378
177
0
28 Feb 2023
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
International Conference on Machine Learning (ICML), 2023
Yasa Syed
Guanyang Wang
488
8
0
10 Jan 2023
Constructing unbiased gradient estimators with finite variance for conditional stochastic optimization
Mathematics and Computers in Simulation (MCS), 2022
T. Goda
Wataru Kitade
286
6
0
04 Jun 2022
Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC
Journal of machine learning research (JMLR), 2022
Guanyang Wang
T. Wang
395
17
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11 Apr 2022
Sequential Bayesian experimental designs via reinforcement learning
Hikaru Asano
OffRL
188
0
0
14 Feb 2022
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2021
Adam Foster
Desi R. Ivanova
Ilyas Malik
Tom Rainforth
289
116
0
03 Mar 2021
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