Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows

18 May 2018

Papers citing "Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows"

50 / 202 papers shown

Title
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy Joeri Hermans François Rozet Antoine Wehenkel Gilles Louppe 15 30 0 29 Aug 2022
Adversarial Bayesian Simulation YueXing Wang Veronika Rovcková GAN BDL 19 5 0 25 Aug 2022
An Optimal Likelihood Free Method for Biological Model Selection Vincent D. Zaballa E. Hui 16 0 0 03 Aug 2022
On minimax density estimation via measure transport Sven Wang Youssef Marzouk OT 16 19 0 20 Jul 2022
Neural Posterior Estimation with Differentiable Simulators Justine Zeghal F. Lanusse Alexandre Boucaud B. Remy E. Aubourg 13 14 0 12 Jul 2022
Guided sequential ABC schemes for intractable Bayesian models Umberto Picchini M. Tamborrino 45 8 0 24 Jun 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 16 11 0 22 Jun 2022
Calibrating Agent-based Models to Microdata with Graph Neural Networks Joel Dyer Patrick W Cannon J. Farmer Sebastian M. Schmon 25 11 0 15 Jun 2022
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization Lorenzo Pacchiardi Ritabrata Dutta TPM BDL UQCV GAN 13 18 0 31 May 2022
Agent-based Simulation of District-based Elections Adway Mitra 9 0 0 28 May 2022
On predictive inference for intractable models via approximate Bayesian computation Marko Jarvenpaa J. Corander TPM 25 2 0 23 Mar 2022
$Variational inference of fractional Brownian motion with linear computational complexity$ Variational inference of fractional Brownian motion with linear computational complexity Hippolyte Verdier Franccois Laurent Alhassan Cassé Christian L. Vestergaard Jean-Baptiste Masson 9 6 0 15 Mar 2022
GATSBI: Generative Adversarial Training for Simulation-Based Inference Poornima Ramesh Jan-Matthis Lueckmann Jan Boelts Álvaro Tejero-Cantero David S. Greenberg P. J. Gonçalves Jakob H. Macke GAN 31 33 0 12 Mar 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 16 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 16 9 0 23 Feb 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 18 42 0 09 Feb 2022
Black-box Bayesian inference for economic agent-based models Joel Dyer Patrick W Cannon J. Farmer Sebastian M. Schmon 11 23 0 01 Feb 2022
Learning Summary Statistics for Bayesian Inference with Autoencoders Carlo Albert S. Ulzega Firat Ozdemir F. Pérez-Cruz Antonietta Mira BDL 33 10 0 28 Jan 2022
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 22 34 0 16 Dec 2021
Measuring the accuracy of likelihood-free inference Aden Forrow R. Baker 6 2 0 15 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 22 31 0 25 Nov 2021
Approximate Bayesian Computation via Classification Yuexi Wang Tetsuya Kaji Veronika Rockova 19 4 0 22 Nov 2021
Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation A. Cole Benjamin Kurt Miller S. Witte Maxwell X. Cai M. Grootes F. Nattino Christoph Weniger 17 40 0 15 Nov 2021
Likelihood-Free Inference in State-Space Models with Unknown Dynamics Alexander Aushev Thong Tran Henri Pesonen Andrew Howes Samuel Kaski 25 1 0 02 Nov 2021
Robot Learning from Randomized Simulations: A Review Fabio Muratore Fabio Ramos Greg Turk Wenhao Yu Michael Gienger Jan Peters AI4CE 10 77 0 01 Nov 2021
Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes D. Warne Thomas P. Prescott Ruth Baker Matthew J. Simpson 12 15 0 26 Oct 2021
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful Joeri Hermans Arnaud Delaunoy François Rozet Antoine Wehenkel Volodimir Begy Gilles Louppe 64 38 0 13 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
Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference François Rozet Gilles Louppe 63 6 0 01 Oct 2021
Simulation-based Bayesian inference for multi-fingered robotic grasping Norman Marlier O. Bruls Gilles Louppe 24 6 0 29 Sep 2021
Identification of Vehicle Dynamics Parameters Using Simulation-based Inference Ali Boyali S. Thompson D. Wong 11 6 0 27 Aug 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
Truncated Marginal Neural Ratio Estimation Benjamin Kurt Miller A. Cole Patrick Forré Gilles Louppe Christoph Weniger 22 37 0 02 Jul 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models Louis Rouillard Demian Wassermann 22 2 0 23 Jun 2021
Deep Bayesian Active Learning for Accelerating Stochastic Simulation D. Wu Ruijia Niu Matteo Chinazzi Alessandro Vespignani Yi-An Ma Rose Yu AI4CE 17 8 0 05 Jun 2021
MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled Trajectories G. Isacchini Natanael Spisak Armita Nourmohammad T. Mora A. Walczak 20 0 0 03 Jun 2021
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds Steven Kleinegesse Michael U. Gutmann FedML 17 25 0 10 May 2021
Fast ABC with joint generative modelling and subset simulation Eliane Maalouf D. Ginsbourger N. Linde 24 0 0 16 Apr 2021
Metropolis-Hastings via Classification Tetsuya Kaji Veronika Rockova 15 8 0 06 Mar 2021
Inverse Gaussian Process regression for likelihood-free inference Hongqiao Wang Ziqiao Ao Tengchao Yu Jinglai Li 15 1 0 21 Feb 2021
Neural Posterior Regularization for Likelihood-Free Inference Dongjun Kim Kyungwoo Song Seung-Jae Shin Wanmo Kang Il-Chul Moon Weonyoung Joo 15 1 0 15 Feb 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 17 33 0 12 Feb 2021
Robust and integrative Bayesian neural networks for likelihood-free parameter inference Fredrik Wrede Robin Eriksson Richard M. Jiang Linda R. Petzold Stefan Engblom A. Hellander Prashant Singh 15 6 0 12 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 96 184 0 12 Jan 2021
Score Matched Neural Exponential Families for Likelihood-Free Inference Lorenzo Pacchiardi Ritabrata Dutta 11 27 0 20 Dec 2020
Learning summary features of time series for likelihood free inference Pedro L. C. Rodrigues Alexandre Gramfort AI4TS 23 4 0 04 Dec 2020
IV-Posterior: Inverse Value Estimation for Interpretable Policy Certificates Tatiana Lopez-Guevara Michael G. Burke Nick K. Taylor Kartic Subr OffRL 8 0 0 30 Nov 2020
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time Benjamin Kurt Miller A. Cole Gilles Louppe Christoph Weniger 11 19 0 27 Nov 2020
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks N. Jeffrey Benjamin Dan Wandelt 9 38 0 11 Nov 2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 10 27 0 11 Nov 2020