Results 51 to 60 of about 157,640 (328)

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Beyond Course Averages: A Generalized Bayesian Hierarchical Framework for Course-Level Learning Evaluation

Journal of Learning Theory and Methodology
Background. Course-level learning assessment in higher education is commonly based on comparisons of average performance indicators, implicitly assuming independence across courses and equal reliability of estimates.
Vicente Montano, Archie Reyes
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

A Bayesian Integrative Mixed Modeling Framework for Analysis of the Multi-Site Adolescent Brain and Cognitive Development Study

Data Science in Science
Integrating high-dimensional, heterogeneous data from multi-site cohort studies with complex hierarchical structures poses significant variable selection and prediction challenges.
Aidan Neher, Apostolos Stamenos, Mark Fiecas, Sandra E. Safo, Thierry Chekouo   +4 more
doaj   +1 more source

A sparse Bayesian hierarchical vector autoregressive model for microbial dynamics in a wastewater treatment plant [PDF]

, 2021
Naomi E. Hannaford, Sarah E. Heaps, Tom M. W. Nye, Thomas P. Curtis, Ben Allen, Andrew Golightly, Darren J. Wilkinson   +6 more
openalex   +1 more source

A hierarchical Bayesian model for syntactic priming [PDF]

CoRR
6 pages; accepted to CogSci ...
Xu, Weijie, Futrell, Richard
openaire   +2 more sources

A hierarchical Bayesian model of pitch framing [PDF]

Journal of Quantitative Analysis in Sports, 2017
Abstract Since the advent of high-resolution pitch tracking data (PITCHf/x), many in the sabermetrics community have attempted to quantify a Major League Baseball catcher’s ability to “frame” a pitch (i.e. increase the chance that a pitch is a called as a strike).
Sameer K. Deshpande, Abraham Wyner
openaire   +2 more sources

Magnetic Textiles: A Review of Materials, Fabrication, Properties, and Applications

Advanced Materials Technologies, EarlyView.
Magnetic textiles (M‐textiles) are emerging as a programmable materials platform that merges magnetic matter with hierarchical textile structures. This article consolidates magnetic material classes, textile architectures, and fabrication and magnetization strategies, revealing structure–property–function relationships that govern magneto‐mechanical ...
Li Ke, Moses Kumi, Xiaoming Tao, Junhong Pu   +3 more
wiley   +1 more source

Bayesian nonparametric hierarchical modeling for multiple membership data in grouped attendance interventions

, 2013
We develop a dependent Dirichlet process (DDP) model for repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each client through a sequence of elements which overlap with ...
Paddock, Susan M., Savitsky, Terrance D.
core   +1 more source

Sensitivity Analysis for Bayesian Hierarchical Models

Bayesian Analysis, 2015
Prior sensitivity examination plays an important role in applied Bayesian analyses. This is especially true for Bayesian hierarchical models, where interpretability of the parameters within deeper layers in the hierarchy becomes challenging. In addition, lack of information together with identifiability issues may imply that the prior distributions for
Roos, Małgorzata, Martins, Thiago G., Held, Leonhard, Rue, Håvard   +3 more
openaire   +4 more sources