Results 61 to 70 of about 9,222 (301)

Machine Learning Unlocks New Directions in Halide Perovskite Research

ChemElectroChem, EarlyView.
GA: This frontispiece visualizes the role of machine learning (ML) in advancing halide perovskite research. It highlights how ML enables the prediction of material properties, guides compositional design, and supports the development of stable, high‐performance perovskite devices for optoelectronic applications, providing new strategies to overcome ...
Hyejin Choe, Heesung Yoon, Inhyang Kim, Soo Young Kim   +3 more
wiley   +1 more source

High-Dimensional Numerical Methods for Nonlocal Models

Mathematics
Nonlocal models offer a unified framework for describing long-range spatial interactions and temporal memory effects. The review briefly outlines several representative physical problems, including anomalous diffusion, material fracture, viscoelastic ...
Yujing Jia, Dongbo Wang, Xu Guo
doaj   +1 more source

Curse of dimensionality on persistence diagrams

Foundations of Data Science
The stability of persistent homology has led to wide applications of the persistence diagram as a trusted topological descriptor in the presence of noise. However, with the increasing demand for high-dimension and low-sample-size data processing in modern science, it is questionable whether persistence diagrams retain their reliability in the presence ...
Hiraoka, Yasuaki, Imoto, Yusuke, Kanazawa, Shu, Liu, Enhao   +3 more
openaire   +2 more sources

Rank‐based estimation of propensity score weights via subclassification

Canadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang, Yuexia Zhang, Thomas S. Richardson, Xiaohua Zhou   +3 more
wiley   +1 more source

Varying Index Coefficient Model for Tail Index Regression

Mathematics
Investigating the causes of extreme events is crucial across various fields. However, existing asymptotic theoretical models often lack flexibility and fail to capture the complex dependency structures inherent in extreme events.
Hongyu An, Boping Tian
doaj   +1 more source

SLIC Superpixel-Based l_2,1-Norm Robust Principal Component Analysis for Hyperspectral Image Classification

Sensors, 2019
Hyperspectral Images (HSIs) contain enriched information due to the presence of various bands, which have gained attention for the past few decades. However, explosive growth in HSIs’ scale and dimensions causes “Curse of dimensionality„
Baokai Zu, Kewen Xia, Tiejun Li, Ziping He, Yafang Li, Jingzhong Hou, Wei Du   +6 more
doaj   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Deep Operator Learning Lessens the Curse of Dimensionality for PDEs [PDF]

, 2023
Ke Chen, Chunmei Wang, Haizhao Yang
openalex   +1 more source

Identification of novel genes regulating the development of the palate

Developmental Dynamics, EarlyView.
Abstract Background The International Mouse Phenotyping Consortium (IMPC) has generated thousands of knockout mouse lines, many of which exhibit embryonic or perinatal lethality. Using micro‐computed tomography (micro‐CT), the IMPC has created and publicly released three‐dimensional image data sets of embryos from these lethal and subviable lines.
Ashwin Bhaskar, Sophie Astrof
wiley   +1 more source

Studying interspecific population synchrony: current status and future perspectives

Ecography, EarlyView.
Interspecific population synchrony, or co‐fluctuations in the population dynamics and demographic parameters of different species, is an important ecological phenomenon with major implications for the stability of communities and ecosystems. It is also central in the context of biodiversity loss, as interspecific synchrony can influence how ecological ...
Ragnhild Bjørkås, Ivar Herfindal, Marlène Gamelon, Aline Magdalena Lee   +3 more
wiley   +1 more source