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

Neural Information Processing Systems (NeurIPS), 2021

3 November 2021

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

37 / 37 papers shown

Title
Online Bayesian Experimental Design for Partially Observed Dynamical Systems Sara Pérez-Vieites Sahel Iqbal Simo Särkkä Dominik Baumann 69 0 0 06 Nov 2025
A Geometric Approach to Optimal Experimental Design Gavin Kerrigan C. A. Naesseth Tom Rainforth OT 239 0 0 16 Oct 2025
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 164 1 0 28 Aug 2025
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition Daolang Huang Xinyi Wen Ayush Bharti Samuel Kaski Luigi Acerbi 185 2 0 08 Jun 2025
PIED: Physics-Informed Experimental Design for Inverse ProblemsInternational Conference on Learning Representations (ICLR), 2025 Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 323 0 0 10 Mar 2025
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design Yasir Zubayr Barlas Kizito Salako 189 1 0 07 Mar 2025
PABBO: Preferential Amortized Black-Box OptimizationInternational Conference on Learning Representations (ICLR), 2025 Xinyu Zhang Daolang Huang Samuel Kaski Julien Martinelli 219 4 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 863 0 0 26 Jan 2025
Amortized Bayesian Experimental Design for Decision-MakingNeural Information Processing Systems (NeurIPS), 2024 Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 360 8 0 03 Jan 2025
Bayesian Experimental Design via Contrastive DiffusionsInternational Conference on Learning Representations (ICLR), 2024 Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 317 5 0 15 Oct 2024
A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design Atlanta Chakraborty Xun Huan Tommie A. Catanach 227 6 0 18 Aug 2024
Amortized Active Learning for Nonparametric Functions Cen-You Li Marc Toussaint Barbara Rakitsch Christoph Zimmer 148 0 0 25 Jul 2024
Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani P. Tigas Stefan Bauer Adam Foster 207 3 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 384 14 0 08 Apr 2024
Nesting Particle Filters for Experimental Design in Dynamical Systems Sahel Iqbal Adrien Corenflos Simo Särkkä Hany Abdulsamad 215 7 0 12 Feb 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive designInternational Conference on Machine Learning (ICML), 2024 Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 257 4 0 11 Feb 2024
Bayesian Active Learning in the Presence of Nuisance ParametersConference on Uncertainty in Artificial Intelligence (UAI), 2023 Sabina J. Sloman Ayush Bharti Julien Martinelli Samuel Kaski 329 4 0 23 Oct 2023
Amortised Experimental Design and Parameter Estimation for User Models of PointingInternational Conference on Human Factors in Computing Systems (CHI), 2023 Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 155 7 0 19 Jul 2023
Variational Sequential Optimal Experimental Design using Reinforcement LearningComputer Methods in Applied Mechanics and Engineering (CMAME), 2023 Wanggang Shen Jiayuan Dong Xun Huan 151 10 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 250 2 0 29 May 2023
Designing Optimal Behavioral Experiments Using Machine LearningeLife (eLife), 2023 Simon Valentin Steven Kleinegesse Neil R. Bramley P. Seriès Michael U. Gutmann Chris Lucas 239 5 0 12 May 2023
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous MonitoringKnowledge Discovery and Data Mining (KDD), 2023 Runzhe Wan Yu Liu James McQueen Doug Hains Rui Song OffRL 114 7 0 02 Apr 2023
Online simulator-based experimental design for cognitive model selectionComputational Brain & Behavior (CBB), 2023 Alexander Aushev Aini Putkonen Grégoire Clarté Suyog H. Chandramouli Luigi Acerbi Samuel Kaski Andrew Howes 154 3 0 03 Mar 2023
Modern Bayesian Experimental DesignStatistical Science (Statist. Sci.), 2023 Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 281 147 0 28 Feb 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental DesignInternational Conference on Machine Learning (ICML), 2023 Desi R. Ivanova Joel Jennings Tom Rainforth Cheng Zhang Adam Foster 280 4 0 27 Feb 2023
Differentiable Multi-Target Causal Bayesian Experimental DesignInternational Conference on Machine Learning (ICML), 2023 Yashas Annadani P. Tigas Desi R. Ivanova Andrew Jesson Y. Gal Adam Foster Stefan Bauer BDL CML 275 14 0 21 Feb 2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian ModelsConference on Uncertainty in Artificial Intelligence (UAI), 2023 Stefan T. Radev Marvin Schmitt Valentin Pratz Umberto Picchini Ullrich Kothe Paul-Christian Bürkner BDL 542 43 0 17 Feb 2023
GFlowNets for AI-Driven Scientific DiscoveryDigital Discovery (DD), 2023 Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 284 74 0 01 Feb 2023
Experimental Design for Multi-Channel Imaging via Task-Driven Feature SelectionInternational Conference on Learning Representations (ICLR), 2022 Stefano B. Blumberg Paddy J. Slator Daniel C. Alexander 351 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 147 2 0 12 Jul 2022
Actively learning to learn causal relationships Chentian Jiang Christopher G. Lucas 117 4 0 20 Jun 2022
Statistical applications of contrastive learning Michael U. Gutmann Steven Kleinegesse Benjamin Rhodes 172 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 184 14 0 08 Mar 2022
Interventions, Where and How? Experimental Design for Causal Models at ScaleNeural Information Processing Systems (NeurIPS), 2022 P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 564 55 0 03 Mar 2022
Bayesian Active Learning for Discrete Latent Variable ModelsNeural Computation (Neural Comput.), 2022 Aditi Jha Zoe C. Ashwood Jonathan W. Pillow 181 11 0 27 Feb 2022
Optimizing Sequential Experimental Design with Deep Reinforcement LearningInternational Conference on Machine Learning (ICML), 2022 Tom Blau Edwin V. Bonilla Iadine Chadès Amir Dezfouli BDL OffRL 380 57 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 267 24 0 02 Jul 2021