Copula Approximate Bayesian Computation Using Distribution Random Forests by George Karabatsos

“…This <i>Stats</i> invited feature article introduces and provides an extensive simulation study of a new approximate Bayesian computation (ABC) framework for estimating the posterior distribution and the maximum likelihood estimate (MLE) of the parameters of models defined by intractable likelihoods, that unifies and extends previous ABC methods proposed separately. …”
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An automatic adaptive method to combine summary statistics in approximate Bayesian computation. by Jonathan U Harrison, Ruth E Baker

“…To infer the parameters of mechanistic models with intractable likelihoods, techniques such as approximate Bayesian computation (ABC) are increasingly being adopted. …”
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Accounting for contact network uncertainty in epidemic inferences with Approximate Bayesian Computation by Maxwell H. Wang, Jukka-Pekka Onnela

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Using Approximate Bayesian Computation to infer sex ratios from acoustic data. by Lisa Lehnen, Wigbert Schorcht, Inken Karst, Martin Biedermann, Gerald Kerth, Sebastien J Puechmaille

“…To meet this demand, we developed a novel approach using Approximate Bayesian Computation (ABC) to infer the sex ratio of populations from acoustic data. …”
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Individual Differences in Cue Weighting in Sentence Comprehension: An Evaluation Using Approximate Bayesian Computation by Himanshu Yadav, Dario Paape, Garrett Smith, Brian W. Dillon, Shravan Vasishth

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Defining Biological Networks for Noise Buffering and Signaling Sensitivity Using Approximate Bayesian Computation by Shuqiang Wang, Yanyan Shen, Changhong Shi, Tao Wang, Zhiming Wei, Hanxiong Li

“…Here, we employ the approximate Bayesian computation (ABC) method based on sequential Monte Carlo (SMC) to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. …”
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Phylodynamic inference and model assessment with approximate bayesian computation: influenza as a case study. by Oliver Ratmann, Gé Donker, Adam Meijer, Christophe Fraser, Katia Koelle

“…We propose using a simulation-based, Bayesian method known as Approximate Bayesian Computation (ABC) to fit and assess phylodynamic models that simulate pathogen evolution and ecology against summaries of these data. …”
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Model Selection and Parameter Estimation for an Improved Approximate Bayesian Computation Sequential Monte Carlo Algorithm by Yue Deng, Yongzhen Pei, Changguo Li, Bin Zhu

“…In this study, we proposed a new algorithm named improved approximate Bayesian computation sequential Monte Carlo algorithm (IABC-SMC) based on approximate Bayesian computation sequential Monte Carlo algorithm (ABC-SMC). …”
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Inferences for Skew-Wiener Degradation Model: Approximate Bayesian Computation via Gibbs-Step and Model Selection by Isyaku Muhammad, Mustapha Muhammad, Ren Aihua, Aiqiang Zhang

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Approximate Bayesian Computation for a Dual-Failure-Modes Models and Its Application to Failure Times Data by Mustapha Muhammad, Badamasi Abba, Jinsen Xiao

Subjects: “…Approximate Bayesian computation…”
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glabcmcmc: a Python package for ABC-MCMC with local and global moves by Xuefei Cao, Shijia Wang, Yongdao Zhou

Subjects: “…Approximate Bayesian Computation…”
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Understanding climate-sensitive tick development and diapause with a structured population model by Kamil Erguler, Anastasios Saratsis, Gerhard Dobler, Lidia Chitimia-Dobler

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Agent‐based versus correlative models of species distributions: Evaluation of predictive performance with real and simulated data by Jukka Sirén, Panu Somervuo, Otso Ovaskainen

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EEMtoolbox: A user‐friendly R package for flexible ensemble ecosystem modelling by Luz Valerie Pascal, Sarah A. Vollert, Malyon D. Bimler, Christopher M. Baker, Maude Vernet, Stefano Canessa, Christopher Drovandi, Matthew P. Adams

Subjects: “…approximate Bayesian computation…”
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Latent class analysis identifies risk groups to model the expected benefits of SARS-CoV-2 interventions among university students by Callum R. K. Arnold, Nita Bharti, Cara Exten, Meg Small, Sreenidhi Srinivasan, Suresh V. Kuchipudi, Vivek Kapur, Matthew J. Ferrari

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Rationalised experiment design for parameter estimation with sensitivity clustering by Harsh Chhajer, Rahul Roy

Subjects: “…Approximate Bayesian computation…”
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Integrating agent‐based models into the ensemble ecosystem modelling framework: A rewilding case study at the Knepp Estate, UK by Emily Neil, Ernesto Carrella, Richard Bailey

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Fuzzy Data Modeling and Parameter Estimation in Two Gamma Populations by Vijay Kumar Lingutla, Nagamani Nadiminti

“…A comprehensive comparison of the Maximum Likelihood Estimation, Lindley&#x2019;s approximation, Approximate Bayesian Computation, and Gibbs sampling is conducted to evaluate their performance. …”
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Chaos in synthetic microbial communities. by Behzad D Karkaria, Angelika Manhart, Alex J H Fedorec, Chris P Barnes

“…Our model selection pipeline uses Approximate Bayesian Computation to first identify oscillatory behaviours as a route to finding chaotic behaviour. …”
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Generative AI for Bayesian Computation by Nick Polson, Vadim Sokolov

“…Generative quantile methods have a number of advantages over traditional approaches such as approximate Bayesian computation (ABC) or GANs. Primarily, quantile architectures are density-free and exploit feature selection using dimensionality reducing summary statistics. …”
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