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Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation

19 February 2020

Papers citing "Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation"

44 / 44 papers shown

Title
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 16 0 0 28 Aug 2025
Adaptive Bayesian Single-Shot Quantum Sensing I. Nikoloska Ruud van Sloun Osvaldo Simeone 30 0 0 22 Jul 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 161 5 0 03 Jan 2025
Mathematical Formalism for Memory Compression in Selective State Space Models Siddhanth Bhat 87 2 0 04 Oct 2024
A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design Atlanta Chakraborty Xun Huan Tommie A. Catanach 115 4 0 18 Aug 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 234 11 0 08 Apr 2024
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo Shijie Zhong Wanggang Shen Tommie A. Catanach Xun Huan 95 6 0 26 Mar 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 114 3 0 11 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 141 0 0 30 Jan 2024
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design Ziqiao Ao Jinglai Li 104 3 0 19 Aug 2023
Amortised Experimental Design and Parameter Estimation for User Models of Pointing Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 95 7 0 19 Jul 2023
Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference Vincent D. Zaballa E. Hui 91 2 0 27 Jun 2023
Variational Sequential Optimal Experimental Design using Reinforcement Learning Wanggang Shen Jiayuan Dong Xun Huan 83 4 0 17 Jun 2023
Bayesian Optimisation Against Climate Change: Applications and Benchmarks Sigrid Passano Hellan Christopher G. Lucas Nigel H. Goddard 148 1 0 07 Jun 2023
Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators Tom Blau Iadine Chadès Amir Dezfouli Daniel M. Steinberg Edwin V. Bonilla 115 1 0 29 May 2023
Designing Optimal Behavioral Experiments Using Machine Learning Simon Valentin Steven Kleinegesse Neil R. Bramley P. Seriès Michael U. Gutmann Chris Lucas 135 4 0 12 May 2023
Online simulator-based experimental design for cognitive model selection Alexander Aushev Aini Putkonen Grégoire Clarté Suyog H. Chandramouli Luigi Acerbi Samuel Kaski Andrew Howes 74 3 0 03 Mar 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 170 108 0 28 Feb 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design Desi R. Ivanova Joel Jennings Tom Rainforth Cheng Zhang Adam Foster 128 3 0 27 Feb 2023
Differentiable Multi-Target Causal Bayesian Experimental Design Yashas Annadani P. Tigas Desi R. Ivanova Andrew Jesson Y. Gal Adam Foster Stefan Bauer BDL CML 136 14 0 21 Feb 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 144 63 0 01 Feb 2023
Batch Multi-Fidelity Active Learning with Budget Constraints Shibo Li J. M. Phillips Xin Yu Robert M. Kirby Shandian Zhe 179 17 0 23 Oct 2022
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection Stefano B. Blumberg Paddy J. Slator Daniel C. Alexander 154 1 0 13 Oct 2022
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development Nghia Duong-Trung Stefan Born Jong Woo Kim M. Schermeyer Katharina Paulick ... Thorben Werner Randolf Scholz Lars Schmidt-Thieme Peter Neubauer Ernesto Martinez 116 23 0 02 Sep 2022
An Optimal Likelihood Free Method for Biological Model Selection Vincent D. Zaballa E. Hui 74 0 0 03 Aug 2022
Efficient Real-world Testing of Causal Decision Making via Bayesian Experimental Design for Contextual Optimisation Desi R. Ivanova Joel Jennings Cheng Zhang Adam Foster CML 71 2 0 12 Jul 2022
Robust Expected Information Gain for Optimal Bayesian Experimental Design Using Ambiguity Sets Jinwook Go T. Isaac 72 14 0 20 May 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 92 9 0 29 Apr 2022
Policy-Based Bayesian Experimental Design for Non-Differentiable Implicit Models Vincent Lim Ellen R. Novoseller Jeffrey Ichnowski Huang Huang Ken Goldberg OffRL 103 13 0 08 Mar 2022
Bayesian Active Learning for Discrete Latent Variable Models Aditi Jha Zoe C. Ashwood Jonathan W. Pillow 116 8 0 27 Feb 2022
Sequential Bayesian experimental designs via reinforcement learning Hikaru Asano OffRL 104 0 0 14 Feb 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning Tom Blau Edwin V. Bonilla Iadine Chadès Amir Dezfouli BDL OffRL 135 50 0 02 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 155 52 0 03 Nov 2021
Bayesian Optimal Experimental Design for Simulator Models of Cognition Simon Valentin Steven Kleinegesse Neil R. Bramley Michael U. Gutmann Chris Lucas 41 4 0 29 Oct 2021
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization Qing Guo Junya Chen Dong Wang Yuewei Yang Xinwei Deng Lawrence Carin Fan Li Jing-Zheng Huang Chenyang Tao 114 23 0 02 Jul 2021
Deep Bayesian Active Learning for Accelerating Stochastic Simulation D. Wu Ruijia Niu Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4CE 237 10 0 05 Jun 2021
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds Steven Kleinegesse Michael U. Gutmann FedML 91 26 0 10 May 2021
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models Jiaxin Zhang Sirui Bi Guannan Zhang 53 0 0 14 Mar 2021
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models Jiaxin Zhang Sirui Bi Guannan Zhang 79 9 0 14 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 124 92 0 03 Mar 2021
Deep Multi-Fidelity Active Learning of High-dimensional Outputs Shibo Li Robert M. Kirby Shandian Zhe AI4CE 103 28 0 02 Dec 2020
Optimal Bayesian experimental design for subsurface flow problems Alexander Tarakanov A. Elsheikh 73 10 0 10 Aug 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 229 104 0 22 Jun 2020
Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs T. Goda Tomohiko Hironaka Wataru Kitade Adam Foster 139 24 0 18 May 2020