Results 211 to 220 of about 116,908 (254)

A composite‐loss graph neural network for the multivariate post‐processing of ensemble weather forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley   +1 more source

Improved generative adversarial networks model for movie dance generation. [PDF]

PLoS One
Lin Z, Feng K.
europepmc   +1 more source

Statistical post‐processing of operational dual‐resolution wind‐speed ensemble forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The performance of raw and post‐processed 50‐member medium‐ and 100‐member extended‐range 10‐m wind‐speed forecasts of the European Centre for Medium‐Range Weather Forecasts and their various dual‐resolution combinations is investigated. Results show that post‐processing improves skill and reduces the differences between the various configurations ...
Sándor Baran, Mária Lakatos
wiley   +1 more source

Physics-Informed Generative Adversarial Networks for Laser Speckle Noise Suppression. [PDF]

Sensors (Basel)
Guo X, Xie F, Yang T, Ming M, Chen T.
europepmc   +1 more source

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño, Alejandro Palacio‐Betancur, Piedad Miranda‐Chiquito, Juan David Amaya, Christian E. Silva, Mariantonieta Gutierrez Soto, Luis Felipe Giraldo   +6 more
wiley   +1 more source

Reconstruction of missing data in transferred generative adversarial networks with small sample data. [PDF]

PLoS One
He J, Chen H, Sheng Z.
europepmc   +1 more source

Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions

Journal of Field Robotics, EarlyView.
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos, Steven Kay, Julia Wajoras, Robert Field, Evridiki V. Ntagiou, Fakher Mohammad, Yang Gao   +6 more
wiley   +1 more source

Enhancing art creation through AI-based generative adversarial networks in educational auxiliary system. [PDF]

Sci Rep
He Y, Zhang S.
europepmc   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Fault detection of high-speed train wheelset bearings based on improved auxiliary classifier generative adversarial networks and VAE. [PDF]

PLoS One
Qiu J, Liu J, Tang M, Zhang D, Li M.
europepmc   +1 more source