A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal
Experiments

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"

17 / 17 papers shown

Title
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
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
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 77 0 28 Feb 2023
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 34 20 0 02 Sep 2022
An Optimal Likelihood Free Method for Biological Model Selection Vincent D. Zaballa E. Hui 34 0 0 03 Aug 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
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
Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni Nouha Dziri Hannes Schulz Geoffrey J. Gordon Philip Bachman Rémi Tachet des Combes SSL 24 29 0 25 Jun 2021
Investigating the Role of Negatives in Contrastive Representation Learning Jordan T. Ash Surbhi Goel A. Krishnamurthy Dipendra Kumar Misra SSL 29 49 0 18 Jun 2021
Active Testing: Sample-Efficient Model Evaluation Jannik Kossen Sebastian Farquhar Y. Gal Tom Rainforth VLM 21 48 0 09 Mar 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 26 64 0 19 Feb 2020