Results 81 to 90 of about 50,616 (261)

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

dockerHDDM: A User-Friendly Environment for Bayesian Hierarchical Drift-Diffusion Modeling

Advances in Methods and Practices in Psychological Science
Drift-diffusion models (DDMs) are pivotal in understanding evidence-accumulation processes during decision-making across psychology, behavioral economics, neuroscience, and psychiatry. Hierarchical DDMs (HDDMs), a Python library for hierarchical Bayesian
Wanke Pan, Haiyang Geng, Lei Zhang, Alexander Fengler, Michael J. Frank, Ru-Yuan Zhang, Hu Chuan-Peng   +6 more
doaj   +1 more source

Bayesian hierarchical vector autoregressive models for patient-level predictive modeling.

PLoS ONE, 2018
Predicting health outcomes from longitudinal health histories is of central importance to healthcare. Observational healthcare databases such as patient diary databases provide a rich resource for patient-level predictive modeling.
Feihan Lu, Yao Zheng, Harrington Cleveland, Chris Burton, David Madigan   +4 more
doaj   +1 more source

Hierarchical Dynamic Beta Model

Revstat Statistical Journal, 2016
We develop a hierarchical dynamic Bayesian beta model for modelling a set of time series of rates or proportions. The proposed methodology enables to combine the information contained in different time series so that we can describe a common underlying ...
Cibele Queiroz Da-Silva , Helio S. Migon   +1 more
doaj   +1 more source

Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design

Advanced Science, EarlyView.
This study reveals how surfactant‐driven interfacial design governs the assembly and stability of protein@MOF composites. Using lipid‐based nonionic surfactants, we modulate protein–MOF interactions to improve encapsulation efficiency, MOF crystallization, and catalytic performance.
Ehsan Rashidniyaghi, Mohammad Khavani, Carlie Coerver, Ruibin Liang, Raheleh Ravanfar   +4 more
wiley   +1 more source

T2T Genome Assembly and Multi‐Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte)

Advanced Science, EarlyView.
A gap‐free genome assembly and multi‐omics comparison of the terrestrial slug Laevichaulis alte with an aquatic relative reveal that expansion of the VEGF family orchestrates mucus production, lipid metabolism, and immune defense—highlighting key molecular innovations for conquering life on land.
Gang Wang, Shaofang He, Zhongkai Wang, Aobo Pang, Xiaoli Sun, Rongchen Liu, Fang Wang, Sisi Chen, Zhijuan Bian, Dongcheng Wei, Liuhan Wu, Siyao Zhao, Qiuting Ji, Yiqi Sun, Niying Sun, Yushinta Fujaya, Boping Tang, Kianann Tan, Daizhen Zhang, Lianfu Chen   +19 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Longitudinal hierarchical Bayesian models of covariate effects on airway and alveolar nitric oxide. [PDF]

Sci Rep, 2023
Weng J, Molshatzki N, Marjoram P, Gauderman WJ, Gilliland FD, Eckel SP.   +5 more
europepmc   +1 more source

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

Advanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

Applying SEM, Exploratory SEM, and Bayesian SEM to Personality Assessments

Psych
Despite the importance of demonstrating and evaluating how structural equation modeling (SEM), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM) work simultaneously, research comparing these analytic ...
Hyeri Hong, Walter P. Vispoel, Alfonso J. Martinez   +2 more
doaj   +1 more source