Neural Networks for Parameter Estimation in Intractable Models

Neural Networks for Parameter Estimation in Intractable Models

29 July 2021

Michael L. Stein

Papers citing "Neural Networks for Parameter Estimation in Intractable Models"

19 / 19 papers shown

Title
Fast Likelihood-Free Parameter Estimation for Lévy Processes Nicolas Coloma William Kleiber 10 0 0 03 May 2025
When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer Emily C. Hector Amanda Lenzi 36 1 0 31 Dec 2024
Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods Julia Walchessen Amanda Lenzi Mikael Kuusela 25 9 0 31 Dec 2024
A Generalized Unified Skew-Normal Process with Neural Bayes Inference Kesen Wang M. Genton SyDa 66 0 0 26 Nov 2024
Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems Rui Zhang O. Chkrebtii Dongbin Xiu 16 0 0 19 Jul 2024
Latent Variable Sequence Identification for Cognitive Models with Neural Bayes Estimation Ti-Fen Pan Jing-Jing Li Bill Thompson Anne Collins BDL 29 0 0 20 Jun 2024
A variational neural Bayes framework for inference on intractable posterior distributions Elliot Maceda Emily C. Hector Amanda Lenzi Brian J. Reich 13 2 0 16 Apr 2024
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 23 14 0 04 Oct 2023
Neural Bayes estimators for censored inference with peaks-over-threshold models J. Richards Matthew Sainsbury-Dale A. Zammit‐Mangion Raphael Huser 17 8 0 27 Jun 2023
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions Nadav Cohen Itzik Klein 3DGS 16 34 0 22 Jun 2023
Universal Approximation and the Topological Neural Network M. Kouritzin Daniel Richard 11 0 0 26 May 2023
Fast parameter estimation of Generalized Extreme Value distribution using Neural Networks Sweta Rai Alexis L Hoffman S. Lahiri D. Nychka S. Sain S. Bandyopadhyay 25 8 0 07 May 2023
Towards black-box parameter estimation Amanda Lenzi Haavard Rue 24 4 0 27 Mar 2023
Likelihood-Free Parameter Estimation with Neural Bayes Estimators Matthew Sainsbury-Dale A. Zammit‐Mangion Raphael Huser 9 30 0 27 Aug 2022
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks J. Richards Raphael Huser 11 11 0 16 Aug 2022
Statistical Deep Learning for Spatial and Spatio-Temporal Data C. Wikle A. Zammit‐Mangion BDL 11 45 0 05 Jun 2022
Spherical Poisson Point Process Intensity Function Modeling and Estimation with Measure Transport T. L. J. Ng A. Zammit‐Mangion 8 3 0 24 Jan 2022
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
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 96 180 0 12 Jan 2021