v1v2 (latest)

A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments

1 November 2019

Papers citing "A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments"

42 / 42 papers shown

Title
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition Daolang Huang Xinyi Wen Ayush Bharti Samuel Kaski Luigi Acerbi 25 0 0 08 Jun 2025
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design Yasir Zubayr Barlas Kizito Salako 61 1 0 07 Mar 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 121 3 0 03 Jan 2025
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 136 1 0 15 Oct 2024
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 93 0 0 15 Oct 2024
Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani P. Tigas Stefan Bauer Adam Foster 78 1 0 26 May 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 186 8 0 08 Apr 2024
BEACON: Bayesian Experimental design Acceleration with Conditional Normalizing flows $-$ a case study in optimal monitor well placement for CO $_2$ sequestration Rafael Orozco A. Gahlot Felix J. Herrmann 52 0 0 28 Mar 2024
Probabilistic Bayesian optimal experimental design using conditional normalizing flows Rafael Orozco Felix J. Herrmann Peng Chen 73 6 0 28 Feb 2024
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities Fengyi Li Ayoub Belhadji Youssef Marzouk 60 2 0 23 Feb 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 83 2 0 11 Feb 2024
Tractable Optimal Experimental Design using Transport Maps Karina Koval Roland Herzog Robert Scheichl OT 113 9 0 15 Jan 2024
Bayesian Active Learning in the Presence of Nuisance Parameters Sabina J. Sloman Ayush Bharti Julien Martinelli Samuel Kaski 88 4 0 23 Oct 2023
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design Ziqiao Ao Jinglai Li 81 2 0 19 Aug 2023
Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference Vincent D. Zaballa E. Hui 74 2 0 27 Jun 2023
Variational Sequential Optimal Experimental Design using Reinforcement Learning Wanggang Shen Jiayuan Dong Xun Huan 66 3 0 17 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 79 1 0 29 May 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 125 88 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 102 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 94 13 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 97 55 0 01 Feb 2023
Design Amortization for Bayesian Optimal Experimental Design Noble Kennamer Steven Walton Alexander Ihler 66 5 0 07 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 84 20 0 02 Sep 2022
An Optimal Likelihood Free Method for Biological Model Selection Vincent D. Zaballa E. Hui 59 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 62 2 0 12 Jul 2022
Robust Expected Information Gain for Optimal Bayesian Experimental Design Using Ambiguity Sets Jinwook Go T. Isaac 58 12 0 20 May 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 66 8 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 71 11 0 08 Mar 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 157 50 0 03 Mar 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning Tom Blau Edwin V. Bonilla Iadine Chadès Amir Dezfouli BDL OffRL 84 44 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 132 48 0 03 Nov 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 93 21 0 02 Jul 2021
Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni Nouha Dziri Hannes Schulz Geoffrey J. Gordon Philip Bachman Rémi Tachet des Combes SSL 79 30 0 25 Jun 2021
Investigating the Role of Negatives in Contrastive Representation Learning Jordan T. Ash Surbhi Goel A. Krishnamurthy Dipendra Kumar Misra SSL 88 54 0 18 Jun 2021
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness Adam Foster Árpi Vezér C. A. Glastonbury Páidí Creed Sam Abujudeh Aaron Sim FaML 41 6 0 15 Jun 2021
Targeted Active Learning for Bayesian Decision-Making Louis Filstroff Iiris Sundin P. Mikkola A. Tiulpin Juuso Kylmäoja Samuel Kaski 71 5 0 08 Jun 2021
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models Jiaxin Zhang Sirui Bi Guannan Zhang 25 0 0 14 Mar 2021
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models Jiaxin Zhang Sirui Bi Guannan Zhang 63 9 0 14 Mar 2021
Active Testing: Sample-Efficient Model Evaluation Jannik Kossen Sebastian Farquhar Y. Gal Tom Rainforth VLM 91 53 0 09 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 78 85 0 03 Mar 2021
Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs T. Goda Tomohiko Hironaka Wataru Kitade Adam Foster 84 23 0 18 May 2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 89 66 0 19 Feb 2020