Results 111 to 120 of about 12,886 (197)

A Generalization Error Bound of Physics‐Informed Neural Networks for Ecological Diffusion Models

Stat, Volume 15, Issue 1, March 2026.
ABSTRACT Ecological diffusion equations (EDEs) are partial differential equations (PDEs) that model spatiotemporal dynamics, often applied to wildlife diseases. Derived from ecological mechanisms, EDEs are useful for forecasting, inference, and decision‐making, such as guiding surveillance strategies for wildlife diseases.
Juan Francisco Mandujano Reyes, Ting Fung Ma, Ian McGahan, Daniel Walsh, Jun Zhu   +4 more
wiley   +1 more source

Asymptotics of the Determinant of Discrete Laplacians on Triangulated and Quadrangulated Surfaces. [PDF]

Commun Math Phys, 2022
Izyurov K, Khristoforov M.
europepmc   +1 more source

Model‐Free Local Partial Correlation

Australian &New Zealand Journal of Statistics, Volume 68, Issue 1, March 2026.
ABSTRACT In the simple linear regression context, partial correlation measures the linear association between two variables, with the linear effects of a third control variable removed. In this paper, we investigate the local partial correlation using a kernel smoothing approach.
Li‐Shan Huang, Chuo‐Ju Yang, Jin‐Ting Zhang   +2 more
wiley   +1 more source

On the real zeroes of half-integral weight Hecke cusp forms. [PDF]

Math Ann
Jääsaari J.
europepmc   +1 more source

On the efficient evaluation of the azimuthal Fourier components of the Green's function for Helmholtz's equation in cylindrical coordinates. [PDF]

J Comput Phys, 2022
Garritano J, Kluger Y, Rokhlin V, Serkh K.   +3 more
europepmc   +1 more source

Beyond Normality: Gain‐Probability Analysis for Symmetric Scale Mixture of Normal Distributions

Australian &New Zealand Journal of Statistics, Volume 68, Issue 1, March 2026.
ABSTRACT Gain‐Probability (G‐P) analysis quantifies the probability that a randomly selected individual from one group scores higher or lower than an individual from another group, by varying magnitudes. While G‐P methods have been developed under normality and various skewed distributions, symmetric heavy‐tailed settings remain largely unexplored ...
Tingting Tong, David Trafimow, Xiangfei Chen, Tonghui Wang, S. T. Boris Choy, Ziyuan Wang   +5 more
wiley   +1 more source

Optimized intrusion detection for IoT networks using Cauchy-Gaussian hybrid evolutionary feature selection. [PDF]

Sci Rep
Saranya T, Indra Priyadharshini S.
europepmc   +1 more source

Extreme values of derivatives of the Riemann zeta function. [PDF]

Mathematika, 2022
Yang D.
europepmc   +1 more source

A Mixture Transition Distribution Modeling for Higher‐Order Circular Markov Processes

Journal of Time Series Analysis, Volume 47, Issue 2, Page 304-320, March 2026.
ABSTRACT This study considers the stationary higher‐order Markov process for circular data by employing the mixture transition distribution modeling. The underlying circular transition distribution is based on Wehrly and Johnson's bivariate joint circular models.
Hiroaki Ogata, Takayuki Shiohama
wiley   +1 more source

Loschmidt echo for deformed Wigner matrices. [PDF]

Lett Math Phys
Erdős L, Henheik J, Kolupaiev O.
europepmc   +1 more source