Variational Bayesian Optimal Experimental Design

13 March 2019

Papers citing "Variational Bayesian Optimal Experimental Design"

29 / 29 papers shown

Title
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 48 0 0 10 Mar 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 113 0 0 20 Jan 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 48 2 0 03 Jan 2025
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 50 0 0 15 Oct 2024
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 30 0 0 15 Oct 2024
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity Analysis Qiao Chen Elise Arnaud Ricardo Baptista O. Zahm 40 1 0 19 Jun 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 54 5 0 08 Apr 2024
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities Fengyi Li Ayoub Belhadji Youssef Marzouk 30 1 0 23 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 36 0 0 30 Jan 2024
OpenBox: A Python Toolkit for Generalized Black-box Optimization Huaijun Jiang Yu Shen Yang Li Beicheng Xu Sixian Du Wentao Zhang Ce Zhang Tengjiao Wang 38 5 0 26 Apr 2023
Prediction-Oriented Bayesian Active Learning Freddie Bickford-Smith Andreas Kirsch Sebastian Farquhar Y. Gal Adam Foster Tom Rainforth 42 29 0 17 Apr 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 77 0 28 Feb 2023
Stability estimates for the expected utility in Bayesian optimal experimental design D. Duong T. Helin Jose Rodrigo Rojo-Garcia 19 10 0 08 Nov 2022
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport Ricardo Baptista Lianghao Cao Joshua Chen Omar Ghattas Fengyi Li Youssef M. Marzouk J. Oden 34 11 0 22 Jun 2022
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning Yang Li Yu Shen Huaijun Jiang Wentao Zhang Zhi-Xin Yang Ce Zhang Tengjiao Wang 36 15 0 06 Jun 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A. Maraval Matthieu Zimmer Antoine Grosnit Rasul Tutunov Jun Wang H. Ammar 30 2 0 27 May 2022
Robust Expected Information Gain for Optimal Bayesian Experimental Design Using Ambiguity Sets Jinwook Go T. Isaac 21 10 0 20 May 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 24 7 0 29 Apr 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 36 48 0 03 Mar 2022
Sequential Bayesian experimental designs via reinforcement learning Hikaru Asano OffRL 18 0 0 14 Feb 2022
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods Desi R. Ivanova Adam Foster Steven Kleinegesse Michael U. Gutmann Tom Rainforth OffRL 21 46 0 03 Nov 2021
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning Wanggang Shen Xun Huan 11 40 0 28 Oct 2021
Automatic Discovery and Description of Human Planning Strategies Julian Skirzyñski Y. Jain Falk Lieder 30 1 0 29 Sep 2021
Test Distribution-Aware Active Learning: A Principled Approach Against Distribution Shift and Outliers Andreas Kirsch Tom Rainforth Y. Gal OOD TTA 39 22 0 22 Jun 2021
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds Steven Kleinegesse Michael U. Gutmann FedML 33 25 0 10 May 2021
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information W. Neiswanger Ke Alexander Wang Stefano Ermon MLAU 37 30 0 19 Apr 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge Florian Hase Matteo Aldeghi Riley J. Hickman L. Roch Alán Aspuru-Guzik 47 105 0 26 Mar 2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 26 64 0 19 Feb 2020