Results 151 to 160 of about 8,116 (238)

Cultural Reflections on African American Religious Experience: A Forum of Emerging Thought

, 2010
Lecture by Anthony Pinn at Lancaster Theological Seminary's first major conference on Black religion, held at the Seminary, Friday and Saturday, April 16 and 17, 2010.
Pinn, Anthony B.
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Physics-Informed Neural Networks Meet Multimodal Large Language Models: Biomechanical Simulation in Aortic Aneurysm. [PDF]

Cyborg Bionic Syst
Zhu S, Abudupataer M, Wang Y, Zhang H, Lai H, Zhu K, Sun Y, Chen N.   +7 more
europepmc   +1 more source

Physics-informed neural network framework for predicting drilling-induced delamination in GFRP composites. [PDF]

PLoS One
Arunadevi M, M S S, B R N M, M C G.
europepmc   +1 more source

Polypyrrole/Graphene/WO₃ Ternary Nanocomposite Sensor Arrays for 3D Ammonia Leakage Reconstruction via Rolling Horizon Data-Assimilated PINNs. [PDF]

Polymers (Basel)
Niu H, Shi Y, Zhao K, Liu J, Yang X, Zheng C.   +5 more
europepmc   +1 more source

FE-PINN Optimization [PDF]

This research enhances a novel finite element physics-informed neural network (FE-PINN) framework in order to optimize efficiency and results. The enhancements include tuning hyperparameters and considering new methodology in constructing the model ...
Bocirnea, Christina
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PINN-FFD: physics- and frequency-informed one-stage detector for brain tumor detection in MRI. [PDF]

Front Oncol
Zhao L, Kang Y, Wang R.
europepmc   +1 more source

Physics-informed deep learning for robust trajectory prediction in automated driving. [PDF]

Sci Rep
Stockem Novo A.
europepmc   +1 more source

Physics-Informed Neural Networks for Gravitational Potential Estimation

reservedMachine learning is continuously evolving through new research and development of network architectures. One notable recent advancement is physics-informed neural networks (PINNs), which are capable of solving complex differential equations and ...
BREJC, GIOVANNI
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Quantitative Prediction of Coal-Gangue Content Using Terahertz Time-Domain Spectroscopy and Physics-Informed Machine Learning. [PDF]

Materials (Basel)
Liu Z, Hu L, Xu J, Yang Y, Li S, Xu Z, Liu L, Li J, Liu H, Ye D.   +9 more
europepmc   +1 more source

Volumetric Ablation of Phenolic Resin in Extreme Environments: A Variable-Property Physics-Informed Neural Network Framework. [PDF]

Polymers (Basel)
Du W, Ma T, Song H.
europepmc   +1 more source