Approximate Bayesian Computational methods

5 January 2011

Papers citing "Approximate Bayesian Computational methods"

50 / 254 papers shown

Title
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biology Henrik Häggström Sebastian Persson Marija Cvijovic Umberto Picchini 19 0 0 15 Apr 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 58 9 0 17 Feb 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 108 2 0 17 Jan 2025
Discovering governing equation in structural dynamics from acceleration-only measurements Calvin Alvares Souvik Chakraborty 17 0 0 18 Jul 2024
Bayesian Structural Model Updating with Multimodal Variational Autoencoder Tatsuya Itoi Kazuho Amishiki Sangwon Lee T. Yaoyama 21 6 0 07 Jun 2024
Inference for the stochastic FitzHugh-Nagumo model from real action potential data via approximate Bayesian computation Adeline Samson M. Tamborrino I. Tubikanec 19 2 0 28 May 2024
Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs Sanmitra Ghosh Paul J. Birrell Daniela De Angelis 35 1 0 02 May 2024
Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods Xuefei Cao Shijia Wang Yongdao Zhou 28 3 0 13 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 49 5 0 08 Apr 2024
Copula Approximate Bayesian Computation Using Distribution Random Forests G. Karabatsos 27 1 0 28 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 14 0 0 30 Jan 2024
A bivariate two-state Markov modulated Poisson process for failure modelling Yoel G. Yera R. Lillo B. F. Nielsen Pepa Ramírez-Cobo Fabrizio Ruggeri 14 9 0 26 Jan 2024
Particle Gibbs for Likelihood-Free Inference of State Space Models with Application to Stochastic Volatility Zhaoran Hou Samuel W.K. Wong 11 0 0 20 Dec 2023
Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inference Marvin Schmitt Stefan T. Radev Paul-Christian Burkner 40 5 0 17 Nov 2023
Fine-Tuning Generative Models as an Inference Method for Robotic Tasks Orr Krupnik Elisei Shafer Tom Jurgenson Aviv Tamar 27 4 0 19 Oct 2023
Sensitivity-Aware Amortized Bayesian Inference Lasse Elsemüller Hans Olischläger Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 13 7 0 17 Oct 2023
An Introduction to the Calibration of Computer Models Richard D. Wilkinson Christopher W. Lanyon 11 0 0 13 Oct 2023
An Extendable Python Implementation of Robust Optimisation Monte Carlo Vasilis Gkolemis Michael U. Gutmann Henri Pesonen 6 1 0 19 Sep 2023
Diffusion Schrödinger Bridges for Bayesian Computation J. Heng Valentin De Bortoli Arnaud Doucet DiffM 20 3 0 27 Aug 2023
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 20 216 0 09 May 2023
Reliable Gradient-free and Likelihood-free Prompt Tuning Maohao Shen S. Ghosh P. Sattigeri Subhro Das Yuheng Bu G. Wornell VLM 44 10 0 30 Apr 2023
Importance is Important: A Guide to Informed Importance Tempering Methods Guanxun Li Aaron Smith Quan Zhou 11 2 0 13 Apr 2023
Correcting Model Misspecification via Generative Adversarial Networks Pronoma Banerjee Manasi V Gude Rajvi J Sampat Sharvari M Hedaoo S. Dhavala Snehanshu Saha 11 0 0 07 Apr 2023
Graph-informed simulation-based inference for models of active matter Namid R Stillman S. Henkes R. Mayor Gilles Louppe 11 1 0 05 Apr 2023
Simulation-based Bayesian inference for robotic grasping Norman Marlier O. Bruls Gilles Louppe 11 4 0 10 Mar 2023
Online simulator-based experimental design for cognitive model selection Alexander Aushev Aini Putkonen Grégoire Clarté Suyog H. Chandramouli Luigi Acerbi Samuel Kaski Andrew Howes 17 2 0 03 Mar 2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models Stefan T. Radev Marvin Schmitt Valentin Pratz Umberto Picchini Ullrich Kothe Paul-Christian Burkner BDL 12 26 0 17 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 31 12 0 27 Jan 2023
Better Together: pooling information in likelihood-free inference David T. Frazier Christopher C. Drovandi David J. Nott 14 1 0 05 Dec 2022
Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference Pierre Glaser Michael Arbel Samo Hromadka Arnaud Doucet A. Gretton 12 2 0 26 Oct 2022
A Geometric Perspective on Bayesian and Generalized Fiducial Inference Yang Liu Jan Hannig Alexander C. Murph 29 0 0 11 Oct 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 20 15 0 01 Aug 2022
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 11 11 0 22 Jun 2022
Generalised Bayesian Inference for Discrete Intractable Likelihood Takuo Matsubara Jeremias Knoblauch F. Briol Chris J. Oates 15 14 0 16 Jun 2022
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity Sirio Legramanti Daniele Durante Pierre Alquier 26 6 0 14 Jun 2022
Approximate confidence distribution computing S. Thornton Wentao Li Min‐ge Xie 17 4 0 03 Jun 2022
Probabilistic learning constrained by realizations using a weak formulation of Fourier transform of probability measures Christian Soize 6 5 0 06 May 2022
On predictive inference for intractable models via approximate Bayesian computation Marko Jarvenpaa J. Corander TPM 12 2 0 23 Mar 2022
Bayesian inference in Epidemics: linear noise analysis S. Bronstein Stefan Engblom R. Marin 9 0 0 21 Mar 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation Joel Dyer Patrick W Cannon Sebastian M. Schmon 8 9 0 23 Feb 2022
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data Jurijs Nazarovs Rudrasis Chakraborty Songwong Tasneeyapant Sathya Ravi Vikas Singh 7 4 0 18 Feb 2022
Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints Christian Soize 9 5 0 10 Feb 2022
Approximate Bayesian Computation with Domain Expert in the Loop Ayush Bharti Louis Filstroff Samuel Kaski TPM 22 7 0 28 Jan 2022
Learning Summary Statistics for Bayesian Inference with Autoencoders Carlo Albert S. Ulzega Firat Ozdemir F. Pérez-Cruz Antonietta Mira BDL 25 10 0 28 Jan 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 19 25 0 20 Dec 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 24 13 0 06 Oct 2021
Simulation-based Bayesian inference for multi-fingered robotic grasping Norman Marlier O. Bruls Gilles Louppe 24 6 0 29 Sep 2021
A Survey of Monte Carlo Methods for Parameter Estimation D. Luengo Luca Martino M. Bugallo Victor Elvira S. Särkkä 6 153 0 25 Jul 2021
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference Niccolò Dalmasso Luca Masserano David Y. Zhao Rafael Izbicki Ann B. Lee 16 5 0 08 Jul 2021
Approximate Bayesian Computation with Path Signatures Joel Dyer Patrick W Cannon Sebastian M. Schmon 11 15 0 23 Jun 2021