Results 91 to 100 of about 11,673,454 (251)

A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]

In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt, Xueyuan Wu, Qing Liu, Xibin Zhang   +3 more
core  

Intracrystalline Void‐Mediated Toughening of Brittle Crystals in Quail Eggshells

Advanced Functional Materials, EarlyView.
In quail eggshells, the high density and disordered arrangement of intracrystalline voids inhibit lattice cleavage, suppress long‐range crack propagation, and promote deformation twinning and quasi‐plasticity, serving as an essential toughening motif. We show that these voids remain within a narrow subcritical size range and therefore predominantly do ...
Jingxiao Zhong, Qihang Wang, Andre E. Vellwock, Sinuhe Perea Puente, Tingting Zhu, Jia Hui Lim, Kadda Medjoubi, Sebastian Hoerl, Erika Griesshaber, Wolfgang W. Schmahl, Yannicke Dauphin, Emeline Raguin, Peter Werner, Francesco Stellacci, Michael V. Swain, Peter Fratzl, Shahrouz Amini   +16 more
wiley   +1 more source

A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation. [PDF]

Multivariate kernel regression is an important tool for investigating the relationship between a response and a set of explanatory variables. It is generally accepted that the performance of a kernel regression estimator largely depends on the choice of ...
Robert D. Brooks, Maxwell L. King, Xibin Zhang   +2 more
core  

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Leveraging Random Effects in Cistrome‐Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer

Advanced Science
Cistrome‐wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to
Mengting Shao, Min Tian, Kaiyang Chen, Hangjin Jiang, Shuting Zhang, Zhenghui Li, Yan Shen, Feng Chen, Baixin Shen, Chen Cao, Ning Gu   +10 more
doaj   +1 more source

Scientific Impact Prediction via Virtual Geography Hawkes Process

Applied Sciences
This brief proposes a novel Virtual-Geography Hawkes Process (VG-Hawkes) to model citation dynamics considering academic networks. The VG-Hawkes model incorporates academic relationships between authors as virtual distances by extending the conventional ...
Babusurya Ganeshbabu, Xin Liu, Akiyoshi Matono, Kyoung-Sook Kim, Xun Shen   +4 more
doaj   +1 more source

Transformation kernel density estimation of actuarial loss functions [PDF]

A transformation kernel density estimator that is suitable for heavy-tailed distributions is discussed. Using a truncated Beta transformation, the choice of the bandwidth parameter becomes straightforward.
Montserrat Guillen (Universitat de Barcelona), Jens Perch Nielsen (City University London), Catalina Bolance (Universitat de Barcelona)   +2 more
core  

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification [PDF]

Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work ...
Alberto Muñoz, Javier González
core  

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source