Likelihood-free inference by ratio estimation

30 November 2016

Papers citing "Likelihood-free inference by ratio estimation"

25 / 25 papers shown

Title
Dequantified Diffusion Schrödinger Bridge for Density Ratio Estimation Wei-Neng Chen Shigui Li J. Li Junmei Yang John Paisley Delu Zeng DiffM OT 62 0 0 08 May 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 66 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
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 32 0 0 22 Jul 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 16 0 0 30 Jan 2024
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos A. Coogan Y. Hezaveh Laurence Perreault Levasseur 27 30 0 06 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 15 10 0 31 Jan 2023
Universal hidden monotonic trend estimation with contrastive learning Edouard Pineau S. Razakarivony Mauricio Gonzalez A. Schrapffer 16 0 0 18 Oct 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy Joeri Hermans François Rozet Antoine Wehenkel Gilles Louppe 13 30 0 29 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 13 11 0 22 Jun 2022
On predictive inference for intractable models via approximate Bayesian computation Marko Jarvenpaa J. Corander TPM 22 2 0 23 Mar 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 14 46 0 08 Mar 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation Joel Dyer Patrick W Cannon Sebastian M. Schmon 13 9 0 23 Feb 2022
Bayesian Sequential Optimal Experimental Design for Nonlinear Models Using Policy Gradient Reinforcement Learning Wanggang Shen Xun Huan 9 39 0 28 Oct 2021
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 29 13 0 06 Oct 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models Louis Rouillard Demian Wassermann 20 2 0 23 Jun 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 15 33 0 12 Feb 2021
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 14 64 0 19 Feb 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 31 117 0 10 Feb 2020
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 10 14 0 04 Jun 2019
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 9 8 0 01 Apr 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 16 40 0 13 Feb 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 18 358 0 18 May 2018
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation Ritabrata Dutta Marcel Schoengens Lorenzo Pacchiardi Avinash Ummadisingu Nicole Widmer Pierre Künzli J. Onnela Antonietta Mira 21 25 0 13 Nov 2017
High-dimensional generalized linear models and the lasso Sara van de Geer 176 748 0 04 Apr 2008