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Bayesian Sequential Optimal Experimental Design for Nonlinear Models
  Using Policy Gradient Reinforcement Learning

Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning

28 October 2021
Wanggang Shen
Xun Huan
ArXivPDFHTML

Papers citing "Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning"

25 / 25 papers shown
Title
Variational Bayesian Optimal Experimental Design with Normalizing Flows
Variational Bayesian Optimal Experimental Design with Normalizing Flows
Jiayuan Dong
Christian L. Jacobsen
Mehdi Khalloufi
Maryam Akram
Wanjiao Liu
Karthik Duraisamy
Xun Huan
BDL
149
8
0
08 Apr 2024
Sequential Bayesian Experimental Design for Implicit Models via Mutual
  Information
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information
Steven Kleinegesse
Christopher C. Drovandi
Michael U. Gutmann
114
28
0
20 Mar 2020
Variational Bayesian Optimal Experimental Design
Variational Bayesian Optimal Experimental Design
Adam Foster
M. Jankowiak
Eli Bingham
Paul Horsfall
Yee Whye Teh
Tom Rainforth
Noah D. Goodman
89
137
0
13 Mar 2019
Efficient Bayesian Experimental Design for Implicit Models
Efficient Bayesian Experimental Design for Implicit Models
Steven Kleinegesse
Michael U. Gutmann
62
50
0
23 Oct 2018
Deep Variational Reinforcement Learning for POMDPs
Deep Variational Reinforcement Learning for POMDPs
Maximilian Igl
L. Zintgraf
T. Le
Frank Wood
Shimon Whiteson
BDL
OffRL
66
261
0
06 Jun 2018
Distributed Distributional Deterministic Policy Gradients
Distributed Distributional Deterministic Policy Gradients
Gabriel Barth-Maron
Matthew W. Hoffman
David Budden
Will Dabney
Dan Horgan
TB Dhruva
Alistair Muldal
N. Heess
Timothy Lillicrap
OffRL
86
480
0
23 Apr 2018
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
499
19,065
0
20 Jul 2017
Noisy Networks for Exploration
Noisy Networks for Exploration
Meire Fortunato
M. G. Azar
Bilal Piot
Jacob Menick
Ian Osband
...
Rémi Munos
Demis Hassabis
Olivier Pietquin
Charles Blundell
Shane Legg
79
895
0
30 Jun 2017
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Ryan J. Lowe
Yi Wu
Aviv Tamar
J. Harb
Pieter Abbeel
Igor Mordatch
140
4,485
0
07 Jun 2017
Parameter Space Noise for Exploration
Parameter Space Noise for Exploration
Matthias Plappert
Rein Houthooft
Prafulla Dhariwal
Szymon Sidor
Richard Y. Chen
Xi Chen
Tamim Asfour
Pieter Abbeel
Marcin Andrychowicz
57
596
0
06 Jun 2017
Stein Variational Policy Gradient
Stein Variational Policy Gradient
Yang Liu
Prajit Ramachandran
Qiang Liu
Jian-wei Peng
69
139
0
07 Apr 2017
Deep Reinforcement Learning: An Overview
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
175
1,539
0
25 Jan 2017
Likelihood-free inference by ratio estimation
Likelihood-free inference by ratio estimation
Owen Thomas
Ritabrata Dutta
J. Corander
Samuel Kaski
Michael U. Gutmann
190
151
0
30 Nov 2016
Sequential Bayesian optimal experimental design via approximate dynamic
  programming
Sequential Bayesian optimal experimental design via approximate dynamic programming
Xun Huan
Youssef M. Marzouk
57
67
0
28 Apr 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
197
8,859
0
04 Feb 2016
Variational Inference: A Review for Statisticians
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
282
4,793
0
04 Jan 2016
Dueling Network Architectures for Deep Reinforcement Learning
Dueling Network Architectures for Deep Reinforcement Learning
Ziyun Wang
Tom Schaul
Matteo Hessel
H. V. Hasselt
Marc Lanctot
Nando de Freitas
OffRL
91
3,755
0
20 Nov 2015
Deep Reinforcement Learning with Double Q-learning
Deep Reinforcement Learning with Double Q-learning
H. V. Hasselt
A. Guez
David Silver
OffRL
170
7,641
0
22 Sep 2015
Continuous control with deep reinforcement learning
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
320
13,248
0
09 Sep 2015
Efficient Bayesian experimentation using an expected information gain
  lower bound
Efficient Bayesian experimentation using an expected information gain lower bound
Panagiotis Tsilifis
R. Ghanem
P. Hajali
47
44
0
30 May 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,776
0
19 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
A Fast and Scalable Method for A-Optimal Design of Experiments for
  Infinite-dimensional Bayesian Nonlinear Inverse Problems
A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems
A. Alexanderian
N. Petra
G. Stadler
Omar Ghattas
61
142
0
22 Oct 2014
Playing Atari with Deep Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
127
12,231
0
19 Dec 2013
Simulation-based optimal Bayesian experimental design for nonlinear
  systems
Simulation-based optimal Bayesian experimental design for nonlinear systems
Xun Huan
Youssef M. Marzouk
81
429
0
20 Aug 2011
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