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Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2021
3 March 2021
Adam Foster
Desi R. Ivanova
Ilyas Malik
Tom Rainforth
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Papers citing
"Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design"
50 / 56 papers shown
Online Bayesian Experimental Design for Partially Observed Dynamical Systems
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BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
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Henry B. Moss
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Edward J. Cripps
David S. Leslie
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BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design
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Sinead Williamson
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Ning Miao
Freddie Bickford-Smith
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Yizhe Zhang
Tom Rainforth
265
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225
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Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design
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Geoffroy Oudoumanessah
Carole Lartizien
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19 Jun 2025
Representative, Informative, and De-Amplifying: Requirements for Robust Bayesian Active Learning under Model Misspecification
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Sabina J. Sloman
Samuel Kaski
OOD
UQCV
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178
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09 Jun 2025
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
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Xinyi Wen
Ayush Bharti
Samuel Kaski
Luigi Acerbi
262
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08 Jun 2025
Optimization of Epsilon-Greedy Exploration
Ethan Che
Hakan Ceylan
James McInerney
Nathan Kallus
223
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03 Jun 2025
Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems
Robert Gruhlke
Matei Hanu
Claudia Schillings
Philipp Wacker
BDL
362
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17 Apr 2025
Dynamic Angle Selection in X-Ray CT: A Reinforcement Learning Approach to Optimal Stopping
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F. Lucka
D. Pelt
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309
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16 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems
International Conference on Learning Representations (ICLR), 2025
Apivich Hemachandra
Gregory Kang Ruey Lau
Szu Hui Ng
Bryan Kian Hsiang Low
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430
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10 Mar 2025
Performance Comparisons of Reinforcement Learning Algorithms for Sequential Experimental Design
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Kizito Salako
277
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07 Mar 2025
PABBO: Preferential Amortized Black-Box Optimization
International Conference on Learning Representations (ICLR), 2025
Xinyu Zhang
Daolang Huang
Samuel Kaski
Julien Martinelli
270
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02 Mar 2025
Actively Inferring Optimal Measurement Sequences
Catherine F. Higham
Paul Henderson
R. Murray-Smith
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333
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25 Feb 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
941
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26 Jan 2025
Bayesian Adaptive Calibration and Optimal Design
Neural Information Processing Systems (NeurIPS), 2024
Rafael Oliveira
Dino Sejdinovic
David Howard
Edwin Bonilla
619
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20 Jan 2025
Amortized Bayesian Experimental Design for Decision-Making
Neural Information Processing Systems (NeurIPS), 2024
Daolang Huang
Yujia Guo
Luigi Acerbi
Samuel Kaski
432
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03 Jan 2025
Bayesian Experimental Design via Contrastive Diffusions
International Conference on Learning Representations (ICLR), 2024
Jacopo Iollo
Christophe Heinkelé
Pierre Alliez
Florence Forbes
398
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15 Oct 2024
Deep Optimal Sensor Placement for Black Box Stochastic Simulations
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Paula Cordero-Encinar
Tobias Schröder
P. Yatsyshin
Andrew Duncan
488
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15 Oct 2024
Amortized Active Learning for Nonparametric Functions
Cen-You Li
Marc Toussaint
Barbara Rakitsch
Christoph Zimmer
188
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25 Jul 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani
P. Tigas
Stefan Bauer
Adam Foster
380
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26 May 2024
Amortized nonmyopic active search via deep imitation learning
Quan Nguyen
Anindya Sarkar
Roman Garnett
357
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23 May 2024
Nesting Particle Filters for Experimental Design in Dynamical Systems
Sahel Iqbal
Adrien Corenflos
Simo Särkkä
Hany Abdulsamad
305
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12 Feb 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design
International Conference on Machine Learning (ICML), 2024
Jacopo Iollo
Christophe Heinkelé
Pierre Alliez
Florence Forbes
367
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11 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta
Wenbo Gong
Chao Ma
Nick Pawlowski
Agrin Hilmkil
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Jianfeng Gao
Stefan Bauer
Danica Kragic
Bernhard Schölkopf
Cheng Zhang
327
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06 Feb 2024
Tractable Optimal Experimental Design using Transport Maps
Inverse Problems (IP), 2024
Karina Koval
Roland Herzog
Robert Scheichl
OT
361
12
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15 Jan 2024
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
International Conference on Machine Learning (ICML), 2023
Marvin Schmitt
Desi R. Ivanova
Daniel Habermann
Baixu Chen
Jie Jiang
Stefan T. Radev
FedML
491
13
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06 Oct 2023
Amortised Design Optimization for Item Response Theory
International Conference on Artificial Intelligence in Education (AIED), 2023
Antti Keurulainen
Isak Westerlund
Oskar Keurulainen
Andrew Howes
182
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19 Jul 2023
Amortised Experimental Design and Parameter Estimation for User Models of Pointing
International Conference on Human Factors in Computing Systems (CHI), 2023
Antti Keurulainen
Isak Westerlund
Oskar Keurulainen
Andrew Howes
271
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19 Jul 2023
Variational Sequential Optimal Experimental Design using Reinforcement Learning
Computer Methods in Applied Mechanics and Engineering (CMAME), 2023
Wanggang Shen
Jiayuan Dong
Xun Huan
273
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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
318
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29 May 2023
Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring
Knowledge Discovery and Data Mining (KDD), 2023
Runzhe Wan
Yu Liu
James McQueen
Doug Hains
Rui Song
OffRL
191
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02 Apr 2023
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches
Ethan Che
Hongseok Namkoong
OffRL
462
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21 Mar 2023
Online simulator-based experimental design for cognitive model selection
Computational Brain & Behavior (CBB), 2023
Alexander Aushev
Aini Putkonen
Grégoire Clarté
Suyog H. Chandramouli
Luigi Acerbi
Samuel Kaski
Andrew Howes
209
3
0
03 Mar 2023
Modern Bayesian Experimental Design
Statistical Science (Statist. Sci.), 2023
Tom Rainforth
Adam Foster
Desi R. Ivanova
Freddie Bickford-Smith
358
175
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28 Feb 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2023
Desi R. Ivanova
Joel Jennings
Tom Rainforth
Cheng Zhang
Adam Foster
351
4
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27 Feb 2023
Differentiable Multi-Target Causal Bayesian Experimental Design
International Conference on Machine Learning (ICML), 2023
Yashas Annadani
P. Tigas
Desi R. Ivanova
Andrew Jesson
Y. Gal
Adam Foster
Stefan Bauer
BDL
CML
327
14
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21 Feb 2023
Black-Box Batch Active Learning for Regression
Andreas Kirsch
315
14
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17 Feb 2023
GFlowNets for AI-Driven Scientific Discovery
Digital Discovery (DD), 2023
Moksh Jain
T. Deleu
Jason S. Hartford
Cheng-Hao Liu
Alex Hernandez-Garcia
Yoshua Bengio
AI4CE
381
78
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01 Feb 2023
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization
Computers and Chemical Engineering (CCE), 2022
Jose Pablo Folch
Robert M. Lee
B. Shafei
David Walz
Calvin Tsay
Mark van der Wilk
Ruth Misener
354
35
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Simulation-Based Parallel Training
Lucas Meyer
Alejandro Ribés
Bruno Raffin
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212
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Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
International Conference on Learning Representations (ICLR), 2022
Stefano B. Blumberg
Paddy J. Slator
Daniel C. Alexander
460
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13 Oct 2022
Design Amortization for Bayesian Optimal Experimental Design
AAAI Conference on Artificial Intelligence (AAAI), 2022
Noble Kennamer
Steven Walton
Alexander Ihler
190
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Active Exploration via Experiment Design in Markov Chains
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Mojmír Mutný
Tadeusz Janik
Andreas Krause
304
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Policy-Based Bayesian Experimental Design for Non-Differentiable Implicit Models
Vincent Lim
Ellen R. Novoseller
Jeffrey Ichnowski
Huang Huang
Ken Goldberg
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244
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Interventions, Where and How? Experimental Design for Causal Models at Scale
Neural Information Processing Systems (NeurIPS), 2022
P. Tigas
Yashas Annadani
Andrew Jesson
Bernhard Schölkopf
Y. Gal
Stefan Bauer
CML
715
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Bayesian Active Learning for Discrete Latent Variable Models
Neural Computation (Neural Comput.), 2022
Aditi Jha
Zoe C. Ashwood
Jonathan W. Pillow
311
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Sequential Bayesian experimental designs via reinforcement learning
Hikaru Asano
OffRL
184
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14 Feb 2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
International Conference on Machine Learning (ICML), 2022
Tom Blau
Edwin V. Bonilla
Iadine Chadès
Amir Dezfouli
BDL
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491
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02 Feb 2022
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