On Nesting Monte Carlo Estimators

18 September 2017

Papers citing "On Nesting Monte Carlo Estimators"

29 / 29 papers shown

Title
Amortized Bayesian Experimental Design for Decision-Making Daolang Huang Yujia Guo Luigi Acerbi Samuel Kaski 59 2 0 03 Jan 2025
Deep Optimal Sensor Placement for Black Box Stochastic Simulations Paula Cordero-Encinar Tobias Schröder P. Yatsyshin Andrew Duncan 55 0 0 15 Oct 2024
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 35 0 0 15 Oct 2024
Does SAM dream of EIG? Characterizing Interactive Segmenter Performance using Expected Information Gain Kuan-I Chung Daniel Moyer VLM 38 0 0 24 Apr 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 59 6 0 08 Apr 2024
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities Fengyi Li Ayoub Belhadji Youssef Marzouk 35 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 36 0 0 08 Dec 2023
Amortised Experimental Design and Parameter Estimation for User Models of Pointing Antti Keurulainen Isak Westerlund Oskar Keurulainen Andrew Howes 33 7 0 19 Jul 2023
Prediction-Oriented Bayesian Active Learning Freddie Bickford-Smith Andreas Kirsch Sebastian Farquhar Y. Gal Adam Foster Tom Rainforth 44 29 0 17 Apr 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 78 0 28 Feb 2023
Optimal randomized multilevel Monte Carlo for repeatedly nested expectations Yasa Syed Guanyang Wang 21 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 48 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 42 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 33 78 0 03 Mar 2021
Efficient Semi-Implicit Variational Inference Vincent Moens Hang Ren A. Maraval Rasul Tutunov Jun Wang H. Ammar 87 6 0 15 Jan 2021
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 60 65 0 23 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 26 19 0 10 Jul 2020
Compositional uncertainty in deep Gaussian processes Ivan Ustyuzhaninov Ieva Kazlauskaite Markus Kaiser Erik Bodin Neill D. F. Campbell Carl Henrik Ek UQCV 41 22 0 17 Sep 2019
Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics Weiguang Peng T. Coleman L. Mentch 29 39 0 25 May 2019
Nested Reasoning About Autonomous Agents Using Probabilistic Programs I. Seaman Jan-Willem van de Meent David Wingate LRM 24 12 0 04 Dec 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 35 196 0 27 Sep 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 39 31 0 20 Jul 2018
Tighter Variational Bounds are Not Necessarily Better Tom Rainforth Adam R. Kosiorek T. Le Chris J. Maddison Maximilian Igl Frank Wood Yee Whye Teh DRL 34 197 0 13 Feb 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 45 684 0 15 Nov 2017
Stability of Noisy Metropolis-Hastings F. Medina-Aguayo Anthony Lee Gareth O. Roberts 67 41 0 24 Mar 2015