Results 81 to 90 of about 24,886 (258)

Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis, A. Carrassi, J. Brajard, L. Bertino, M. Broccoli, D. Iovino, T.S. Finn, M. Bocquet   +7 more
wiley   +1 more source

Covariance-based soft clustering of functional data based on the Wasserstein-Procrustes metric [PDF]

, 2022
V. Masarotto, G. Masarotto
openalex   +1 more source

Metric Currents and Geometry of Wasserstein Spaces

Rendiconti del Seminario Matematico della Università di Padova, 2010
We investigate some geometric aspects of Wasserstein spaces through the continuity equation as worked out in mass transportation theory. By defining a suitable homology on the flat torus \mathbb T^n , we prove that the space
openaire   +2 more sources

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

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source

No-Reference Hyperspectral Image Quality Assessment via Ranking Feature Learning

Remote Sensing
In hyperspectral image (HSI) reconstruction tasks, due to the lack of ground truth in real imaging processes, models are usually trained and validated on simulation datasets and then tested on real measurements captured by real HSI imaging systems ...
Yuyan Li, Yubo Dong, Haoyong Li, Danhua Liu, Fang Xue, Dahua Gao   +5 more
doaj   +1 more source

Bridging classical data assimilation and optimal transport: the 3D-Var case [PDF]

Nonlinear Processes in Geophysics
Because optimal transport (OT) acts as displacement interpolation in physical space rather than as interpolation in value space, it can avoid double-penalty errors generated by mislocations of geophysical fields.
M. Bocquet, P. J. Vanderbecken, A. Farchi, J. Dumont Le Brazidec, Y. Roustan   +4 more
doaj   +1 more source

Optimal Scheduling of Data Centre Integrated Energy Systems Considering Electric‐Thermal Demand Response Under Icing Uncertainty

Energy Internet, EarlyView.
ABSTRACT Extreme icing disasters increasingly undermine the reliability of integrated power and heat networks by causing line outages, supply shortages and sharp thermal load fluctuations. To address these challenges, this paper proposes a comprehensive optimisation framework that exploits the spatiotemporal flexibility of data centres for coordinated ...
Yan Wang, Hui Hou, Zhengguo Wang, Wenzhe Zheng, Zhengtian Li, Xiangning Lin, Wu Chen   +6 more
wiley   +1 more source

Beyond the next step: A multi‐criteria generative validation framework for step selection functions

Methods in Ecology and Evolution, EarlyView.
Abstract Step‐selection functions (SSFs), typically fitted using step‐selection analysis (SSA) or integrated step‐selection analysis (iSSA) are widely used to infer habitat selection and movement kernels from high‐frequency telemetry data, but most standard validation tools focus on one‐step‐ahead prediction and do not guarantee that fitted models ...
Aurélien Nicosia
wiley   +1 more source

Metric extrapolation in the Wasserstein space

Calculus of Variations and Partial Differential Equations
In this article we study a variational problem providing a way to extend for all times minimizing geodesics connecting two given probability measures, in the Wasserstein space. This is simply obtained by allowing for negative coefficients in the classical variational characterization of Wasserstein barycenters.
Gallouët, Thomas, Natale, Andrea, Todeschi, Gabriele   +2 more
openaire   +4 more sources