Results 111 to 120 of about 10,137 (199)
Topics in Cognitive Science, EarlyView.Abstract Recent studies suggest that learners who are asked to predict the outcome of an event learn more than learners who are asked to evaluate it retrospectively or not at all. One possible explanation for this “prediction boost” is that it helps learners engage metacognitive reasoning skills that may not be spontaneously leveraged, especially for ...
Joseph A. Colantonio +4 more
wiley +1 more source
A Dynamic Model for Extreme Hourly Precipitation
Environmetrics, Volume 37, Issue 3, April 2026.ABSTRACT Despite the scarcity of comprehensive studies at a global scale, many regional analyses report increases in extreme hourly precipitation values. The growing interest in assessing trends in extreme hourly precipitation has outpaced the development of new statistical tools tailored to their features. Typical analyses employ Extreme Value Theory (
Debbie J. Dupuis +2 more
wiley +1 more source
Scour‐Conditioned Seismic Fragility Analysis of Monopile‐Supported Offshore Wind Turbines
Earthquake Engineering &Structural Dynamics, Volume 55, Issue 4, Page 947-967, 10 April 2026.ABSTRACT Monopile‐supported offshore wind turbines (MS‐OWTs) are increasingly deployed in seismic coastal regions, where they face compound risks from earthquake loading and seabed scour. While past studies have addressed these hazards separately, seismic fragility under evolving scour conditions remains insufficiently understood. This study introduces
Francisco Pinto +3 more
wiley +1 more source
Anomaly Detection for Structural and Functional Connectivity in Glioma Patients
NMR in Biomedicine, Volume 39, Issue 4, April 2026.Structural connectivity (SC) and functional connectivity (FC) provide crucial insights into glioma‐brain interactions. This study uses variational autoencoder to integrate FC and SC, detect anomalies, and investigate connectivity impairments in networks proximal and distal to the tumor.
Maria Colpo +6 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
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract The variational autoencoder (VAE), a deep generative model, can extract a good feature representation for clustering from complex data; however, the use of this algorithm in the geophysical fluid circulation has been limited. The sample size for a geophysical phenomenon is generally small because of a large dimensional size, especially for ...
Kunihiro Aoki +7 more
wiley +1 more source
Technical Notes on Kullback-Leibler Divergence
, 2018 I provide some technical notes regarding the Kullback-Leibler divergence. Derivations of the Kullback-Leibler divergence are provided for Bernoulli, Geometric, Poisson, Exponential, and Normal distributions.
openaire +2 more sources
Artificial intelligence streamlines scientific discovery of drug–target interactions
British Journal of Pharmacology, Volume 183, Issue 8, Page 1673-1690, April 2026.Abstract Drug discovery is a complicated process through which new therapeutics are identified to prevent and treat specific diseases. Identification of drug–target interactions (DTIs) stands as a pivotal aspect within the realm of drug discovery and development. The traditional process of drug discovery, especially identification of DTIs, is marked by
Yuxin Yang, Feixiong Cheng
wiley +1 more source
Bi‐Directional Recurrent Attentional Topic Model Using Flexible Priors
Computational Intelligence, Volume 42, Issue 2, April 2026.ABSTRACT This article presents extensions to the Bi‐Directional Recurrent Attentional Topic Model (bi‐RATM) framework, a Dirichlet‐based model used in text document analysis. The allocation of topics to a sentence in a document is determined by its content as well as the topics of its neighboring sentences, and the weighting is typically variable. Many
Pantea Koochemeshkian, Nizar Bouguila
wiley +1 more source
Coarse‐to‐Fine Spatial Modeling: A Scalable, Machine‐Learning‐Compatible Framework
Geographical Analysis, Volume 58, Issue 2, April 2026.ABSTRACT This study proposes coarse‐to‐fine spatial modeling (CFSM) as a scalable and machine learning‐compatible alternative to conventional spatial process models. Unlike conventional covariance‐based spatial models, CFSM represents spatial processes using a multiscale ensemble of local models.
Daisuke Murakami +5 more
wiley +1 more source