Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods

3 November 2021

Papers citing "Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods"

32 / 32 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
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design Yasir Zubayr Barlas Kizito Salako 32 0 0 07 Mar 2025
PABBO: Preferential Amortized Black-Box Optimization Xinyu Zhang Daolang Huang Samuel Kaski Julien Martinelli 34 0 0 02 Mar 2025
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies from Simulated Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer OffRL 167 0 0 26 Jan 2025
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 44 2 0 03 Jan 2025
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 30 0 0 15 Oct 2024
A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design Atlanta Chakraborty Xun Huan Tommie A. Catanach 37 3 0 18 Aug 2024
Amortized Active Learning for Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer 28 0 0 25 Jul 2024
Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani P. Tigas Stefan Bauer Adam Foster 42 0 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 54 5 0 08 Apr 2024
Nesting Particle Filters for Experimental Design in Dynamical Systems Sahel Iqbal Adrien Corenflos Simo Särkkä Hany Abdulsamad 30 2 0 12 Feb 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 21 1 0 11 Feb 2024
Bayesian Active Learning in the Presence of Nuisance Parameters Sabina J. Sloman Ayush Bharti Julien Martinelli Samuel Kaski 28 3 0 23 Oct 2023
Amortised Experimental Design and Parameter Estimation for User Models of Pointing Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 28 7 0 19 Jul 2023
Variational Sequential Optimal Experimental Design using Reinforcement Learning Wanggang Shen Jiayuan Dong Xun Huan 21 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 18 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 27 2 0 12 May 2023
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring Runzhe Wan Yu Liu James McQueen Doug Hains Rui Song OffRL 30 4 0 02 Apr 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 27 2 0 03 Mar 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 77 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 34 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 31 13 0 21 Feb 2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models Stefan T. Radev Marvin Schmitt Valentin Pratz Umberto Picchini Ullrich Kothe Paul-Christian Bürkner BDL 34 29 0 17 Feb 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 34 45 0 01 Feb 2023
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection Stefano B. Blumberg Paddy J. Slator Daniel C. Alexander 42 1 0 13 Oct 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 29 2 0 12 Jul 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 24 7 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 30 10 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 36 48 0 03 Mar 2022
Bayesian Active Learning for Discrete Latent Variable Models Aditi Jha Zoe C. Ashwood Jonathan W. Pillow 16 7 0 27 Feb 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning Tom Blau Edwin V. Bonilla Iadine Chadès Amir Dezfouli BDL OffRL 24 37 0 02 Feb 2022
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 29 19 0 02 Jul 2021