On Nesting Monte Carlo Estimators

18 September 2017

Papers citing "On Nesting Monte Carlo Estimators"

24 / 24 papers shown

Title
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 48 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
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 50 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
Human-in-the-Loop Visual Re-ID for Population Size Estimation Gustavo Pérez Daniel Sheldon Grant Van Horn Subhransu Maji 28 0 0 08 Dec 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
Prediction-Oriented Bayesian Active Learning Freddie Bickford-Smith Andreas Kirsch Sebastian Farquhar Y. Gal Adam Foster Tom Rainforth 42 29 0 17 Apr 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 77 0 28 Feb 2023
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations Yasa Syed Guanyang Wang 14 6 0 10 Jan 2023
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport Ricardo Baptista Lianghao Cao Joshua Chen Omar Ghattas Fengyi Li Youssef M. Marzouk J. Oden 37 11 0 22 Jun 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
Sequential Bayesian experimental designs via reinforcement learning Hikaru Asano OffRL 18 0 0 14 Feb 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
GaussED: A Probabilistic Programming Language for Sequential Experimental Design Matthew A. Fisher Onur Teymur Chris J. Oates 40 1 0 15 Oct 2021
Test Distribution-Aware Active Learning: A Principled Approach Against Distribution Shift and Outliers Andreas Kirsch Tom Rainforth Y. Gal OOD TTA 39 22 0 22 Jun 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 28 78 0 03 Mar 2021
Efficient Semi-Implicit Variational Inference Vincent Moens Hang Ren A. Maraval Rasul Tutunov Jun Wang H. Ammar 85 6 0 15 Jan 2021
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 52 65 0 23 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 24 19 0 10 Jul 2020
Nested Reasoning About Autonomous Agents Using Probabilistic Programs I. Seaman Jan-Willem van de Meent David Wingate LRM 19 12 0 04 Dec 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 26 31 0 20 Jul 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Stability of Noisy Metropolis-Hastings F. Medina-Aguayo Anthony Lee Gareth O. Roberts 62 41 0 24 Mar 2015