Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network

8 October 2015

Papers citing "Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network"

21 / 21 papers shown

Title
ConDiSim: Conditional Diffusion Models for Simulation Based Inference Mayank Nautiyal Andreas Hellander Prashant Singh DiffM 32 0 0 13 May 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 85 9 0 17 Feb 2025
Deep Generative Quantile Bayes Jungeum Kim Percy S. Zhai Veronika Rockova 51 0 0 10 Oct 2024
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 36 15 0 04 Oct 2023
Minimax optimal testing by classification P. R. Gerber Yanjun Han Yury Polyanskiy 33 3 0 19 Jun 2023
Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space Diane Oyen Michal Kucer N. Hengartner H. Singh NoLa OOD 36 13 0 02 Jun 2022
pyABC: Efficient and robust easy-to-use approximate Bayesian computation Yannik Schälte Emmanuel Klinger Emad Alamoudi Jan Hasenauer 19 22 0 24 Mar 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation Joel Dyer Patrick W Cannon Sebastian M. Schmon 32 9 0 23 Feb 2022
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 33 31 0 25 Nov 2021
TIP: Task-Informed Motion Prediction for Intelligent Vehicles Xin Huang Guy Rosman A. Jasour Stephen G. McGill J. Leonard B. Williams 40 15 0 17 Oct 2021
Neural Networks for Parameter Estimation in Intractable Models Amanda Lenzi J. Bessac J. Rudi Michael L. Stein BDL 26 50 0 29 Jul 2021
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 30 79 0 20 Oct 2020
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation Mattias Åkesson Prashant Singh Fredrik Wrede Andreas Hellander BDL 30 33 0 31 Jan 2020
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 37 14 0 26 Aug 2019
Spectral Density-Based and Measure-Preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs E. Buckwar M. Tamborrino I. Tubikanec 21 36 0 04 Mar 2019
Adaptive Gaussian Copula ABC Yanzhi Chen Michael U. Gutmann TPM 23 27 0 27 Feb 2019
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation Samuel Wiqvist Pierre-Alexandre Mattei Umberto Picchini J. Frellsen BDL 30 32 0 29 Jan 2019
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 24 47 0 12 Jun 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 34 25 0 13 Nov 2017
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 34 240 0 06 Nov 2017
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 42 145 0 30 Nov 2016