Results 61 to 70 of about 3,751,804 (256)

Classification of points in 2-dimensional lattice based on realisations of Gaussian random fields

Lietuvos Matematikos Rinkinys, 1997
There is not abstract.
Kęstutis Dučinskas, Jūratė Šaltytė
doaj   +1 more source

Macroscaling limit theorems for filtered spatiotemporal random fields

, 2013
This article addresses the problem of defining a general scaling setting in which Gaussian and non-Gaussian limit distributions of linear random fields can be obtained. The linear random fields considered are defined by the convolution of a Green kernel,
Anh, Vo, Anh, V. V., Ruiz-Medina, M. D., Leonenko, Nikolai N., Ruiz-Medina, Maria, Leonenko, Nikolai   +5 more
core   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Learning generative texture models with extended Fields-of-Experts [PDF]

, 2009
We evaluate the ability of the popular Field-of-Experts (FoE) to model structure in images. As a test case we focus on modeling synthetic and natural textures.
Geoffrey E. Hinton, Christopher K.I. Williams, Hinton, Geoffrey E., Heess, Nicolas, Williams, Christopher K. I., Nicolas Heess   +5 more
core   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

High-risk human papillomavirus cervical infection prevalence: a nationwide retrospective study comparing opportunistic and organised screening, France, 2020 to 2023

Eurosurveillance
BACKGROUND In France, cervical cancer screening for females aged 30­–65 years primarily tests for high-risk (HR) human papillomavirus (HPV) infections. AIM We aimed to map the prevalence of cervical infections caused by HPV16 and/or 18, or by any of 12 ...
Samuel Alizon
doaj   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Computations With Gaussian Random Fields [PDF]

, 1999
An approach to computational problems associated with generation and estimation of large Gaussian fields is studied. Fast algorithms for matrix operations on circulant matrices are presented, and a connection between such matrices and covariance matrices
Kozintsev, Boris
core   +1 more source

Simulating mixture of sub-Gaussian spatial data [PDF]

AUT Journal of Mathematics and Computing
Spatial datasets may contain extreme values and exhibit heavy tails. So, the Gaussianity assumption for the corresponding random field is not reasonable. A sub-Gaussian α-stable (SGαS) random field may be more suitable as a model for heavy-tailed spatial
Seyedeh Somayeh Mousavi, Adel Mohammadpour   +1 more
doaj   +1 more source

Propriety of Posteriors in Structured Additive Regression Models: Theory and Empirical Evidence [PDF]

, 2006
Structured additive regression comprises many semiparametric regression models such as generalized additive (mixed) models, geoadditive models, and hazard regression models within a unified framework.
Kneib, Thomas, Fahrmeir, Ludwig
core   +1 more source