Results 121 to 130 of about 3,027 (198)

MWG-UNet++: Hybrid Transformer U-Net Model for Brain Tumor Segmentation in MRI Scans

Bioengineering
The accurate segmentation of brain tumors from medical images is critical for diagnosis and treatment planning. However, traditional segmentation methods struggle with complex tumor shapes and inconsistent image quality which leads to suboptimal results.
Yu Lyu, Xiaolin Tian
doaj   +1 more source

A Comparative Review of Specification Tests for Diffusion Models

International Statistical Review, Volume 94, Issue 2, Page 347-381, August 2026.
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez, D. Diz‐Castro, M. Febrero‐Bande, W. González‐Manteiga   +3 more
wiley   +1 more source

Carbon-aware mobile energy storage system scheduling in active power distribution systems under PV and traffic uncertainties

Energy Reports
Carbon emission flow (CEF) is a promising approach for assessing both generation-and consumption-side carbon footprints in the power system sector. In this study, we propose a carbon-aware mobile energy storage system (MESS) scheduling framework that ...
Panggah Prabawa, Dae-Hyun Choi
doaj   +1 more source

Neural‐Initialized Newton: Accelerating Nonlinear Finite Elements via Operator Learning

International Journal for Numerical Methods in Engineering, Volume 127, Issue 14, 30 July 2026.
ABSTRACT We propose a Newton‐based scheme, initialized by neural operator predictions, to accelerate the parametric solution of nonlinear problems in computational solid mechanics. First, a physics‐informed neural operator based on conditional neural fields or Fourier neural operators is trained to approximate the nonlinear parametric solution of the ...
Kianoosh Taghikhani, Yusuke Yamazaki, Jerry Paul Varghese, Markus Apel, Reza Najian Asl, Shahed Rezaei   +5 more
wiley   +1 more source

Distributional robustness based on Wasserstein-metric approach for humanitarian logistics problem under road disruptions

Operations Research Perspectives
Humanitarian logistics plays a vital role in disaster management. However, it often faces the challenge of unpredictable road conditions when solving relief prepositioning problems to effectively respond to natural disasters.
Yingying Gao, Xianghai Ding, Wuyang Yu
doaj   +1 more source

Analysis of dynamically stable patterns in a maze-like corridor using the Wasserstein metric. [PDF]

Sci Rep, 2018
Ishiwata R, Kinukawa R, Sugiyama Y.
europepmc   +1 more source

Domain adaptation via Wasserstein distance and discrepancy metric for chest X-ray image classification

Scientific Reports
Deep learning technology can effectively assist physicians in diagnosing chest radiographs. Conventional domain adaptation methods suffer from inaccurate lesion region localization, large errors in feature extraction, and a large number of model ...
Bishi He, Yuanjiao Chen, Darong Zhu, Zhe Xu   +3 more
doaj   +1 more source

Learning and inference with Wasserstein metrics

, 2018
This thesis develops new approaches for three problems in machine learning, using tools from the study of optimal transport (or Wasserstein) distances between probability distributions. Optimal transport distances capture an intuitive notion of similarity between distributions, by incorporating the underlying geometry of the domain of the distributions.
openaire   +1 more source

Fast and interpretable quantification of biological shape heterogeneity via stratified Wasserstein kernel. [PDF]

PLoS Comput Biol
Zhao W, Sutherland DJ, Dao Duc K.
europepmc   +1 more source

Robust topology and dispatch optimization for renewable distribution networks with electric vehicle mobility uncertainty. [PDF]

Sci Rep
Xu L, Jiang J, Hu S, Wang T, Dong J.
europepmc   +1 more source