Results 91 to 100 of about 157,640 (328)

ggmcmc: Analysis of MCMC Samples and Bayesian Inference

Journal of Statistical Software, 2016
ggmcmc is an R package for analyzing Markov chain Monte Carlo simulations from Bayesian inference. By using a well known example of hierarchical/multilevel modeling, the article reviews the potential uses and options of the package, ranging from ...
Xavier Fernández-i-Marín
doaj   +1 more source

A Hierarchical Bayesian Implementation of the Experience-Weighted Attraction Model

Computational Psychiatry, 2020
Social and decision-making deficits are often the first symptoms of neuropsychiatric disorders. In recent years, economic games, together with computational models of strategic learning, have been increasingly applied to the characterization of ...
Zhihao Zhang, Saksham Chandra, Andrew Kayser, Ming Hsu, Joshua L. Warren   +4 more
doaj   +1 more source

Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach [PDF]

This paper uses an infinite hidden Markov model (IHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks.
Markus Jochmann
core  

Bayesian hierarchical modelling approaches for combining information from multiple data sources to produce annual estimates of national immunization coverage [PDF]

, 2022
C. Edson Utazi, Warren C. Jochem, Marta Gacic-Dobo, Padraic Murphy, Sujit K. Sahu, Carolina M. Danovaro-Holliday, Andrew J. Tatem   +6 more
openalex   +1 more source

Bayesian hierarchical statistical SIRS models

Statistical Methods & Applications, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lili Zhuang, Noel Cressie
openaire   +3 more sources

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source