Results 171 to 180 of about 7,662,414 (297)
Borrowing Strength and Borrowing Index for Bayesian Hierarchical Models. [PDF]
Comput Stat Data Anal, 2020 Xu G, Zhu H, Lee JJ.
europepmc +1 more source
Physics‐Guided Modeling of Temperature‐Dependent Electrical Conductivity of Functional Oxides
Advanced Intelligent Discovery, EarlyView.This complete workflow presents an automated, data‐driven screening of functional oxides based on their predicted electrical conductivity. A curated dataset is fed into TriCondNet, a charge‐transport, physics‐guided neural network that classifies an input composition's conduction mechanism and then simulates its conductivity–temperature profile.
Elias Assaad +6 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Data scarcity is a critical bottleneck for machine learning in applied chemistry. We show that physics‐informed descriptors enable a simple linear model to predict the deblocking temperatures of capped diisocyanates to within 11 °C from just 19 measurements, demonstrating that embedding physical insight into descriptors, rather than relying on ...
Remsha Rafiq +9 more
wiley +1 more source
Bayesian inference for Hidden Markov Model [PDF]
Hidden Markov Models can be considered an extension of mixture models, allowing for dependent observations. In a hierarchical Bayesian framework, we show how Reversible Jump Markov Chain Monte Carlo techniques can be used to estimate the parameters of ...
Luisa Scaccia, Rosella Castellano
core
Advanced Intelligent Systems, EarlyView.A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang +4 more
wiley +1 more source
Detection of fish movement patterns across management unit boundaries using age-structured Bayesian hierarchical models with tag-recovery data. [PDF]
PLoS One, 2020 Bi R, Zhou C, Jiao Y.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Multi‐Stage Social Value Orientation‐Based Lane‐Changing Driving for Autonomous Vehicles
Advanced Intelligent Systems, EarlyView.A multi‐stage SVO framework is developed to dynamically infer the social preferences of surrounding vehicles from human driving data. By combining offline learning, online SVO estimation, temporal intention tracking, and interaction‐aware planning, the framework enables autonomous vehicles to adapt lane‐changing decisions and trajectories to evolving ...
Nongrui Qin +4 more
wiley +1 more source
Tracheal chambers as a key innovation for high‐frequency emission in bat echolocation
The Anatomical Record, EarlyView.Abstract Key innovations are pivotal for biodiversity and facilitating evolutionary success, enabling organisms' adaptation to various ecological niches through the diversification of phenotypic traits. In mammals, notable adaptations include evolving hypsodonty for grazing on grasses and, for bats, evolving echolocation and wing acquisition.
Nicolas L. M. Brualla +7 more
wiley +1 more source