Results 121 to 130 of about 59,513 (222)
Infants and Mobiles: Developing an Understanding of Cause and Effect
Developmental Science, Volume 29, Issue 4, July 2026.ABSTRACT In the mobile conjugate reinforcement paradigm, an infant's leg is connected to a mobile via a string, allowing the infant to move the mobile via moving their leg. Over a few minutes, infants exhibit an increase in the frequency of movement of the connected leg.
Xia Xu, Jochen Triesch
wiley +1 more source
A Deep-Learning-Based Health Indicator Constructor Using Kullback-Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures. [PDF]
Sensors (Basel), 2022 Nguyen TK, Ahmad Z, Kim JM.
europepmc +1 more source
Developmental Science, Volume 29, Issue 4, July 2026.ABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Ruolan Leslie Famularo +3 more
wiley +1 more source
Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography. [PDF]
Front Oncol, 2023 Yu J +6 more
europepmc +1 more source
Marine Mammal Science, Volume 42, Issue 3, July 2026.ABSTRACT Automated detection and classification of marine mammal vocalizations is critical for conservation and management efforts but is hindered by limited annotated datasets and the acoustic complexity of real‐world marine environments. Data augmentation has proven to be an effective strategy to address this limitation by increasing dataset ...
Bruno Padovese +3 more
wiley +1 more source
Covariance Structure Modeling of Engineering Demand Parameters in Cloud‐Based Seismic Analysis
Earthquake Engineering &Structural Dynamics, Volume 55, Issue 7, Page 1533-1551, June 2026.ABSTRACT Probabilistic seismic demand modeling aims to estimate structural demand as a function of ground motion intensity—a critical stage in seismic risk assessment. Although many models exist to describe the structural demand, few consider the covariance among engineering demand parameters, potentially overlooking a key factor in improving the ...
Archie Rudman +3 more
wiley +1 more source
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT This study extends a deep learning framework for the inverse reconstruction of open‐cell porous metamaterials targeting specific hydraulic properties such as porosity and intrinsic permeability. Building on our recent work that employed a property‐variational autoencoder (pVAE) for structure–property mapping, the current contribution examines ...
Phu Thien Nguyen +3 more
wiley +1 more source
On MAP Estimates and Source Conditions for Drift Identification in SDEs
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck +3 more
wiley +1 more source
Viewpoint Selection for 3D-Games with f-Divergences
EntropyIn this paper, we present a novel approach for the optimal camera selection in video games. The new approach explores the use of information theoretic metrics f-divergences, to measure the correlation between the objects as viewed in camera frustum and ...
Micaela Y. Martin +2 more
doaj +1 more source
On the Foundational Arguments of Sufficient Dimension Reduction
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley +1 more source