Results 31 to 40 of about 4,250,733 (158)
Probabilistic machine learning and data-driven methods gradually show their high efficiency in solving the forward and inverse problems of partial differential equations (PDEs).
Wei Gu, Wenbo Zhang, Yaling Han
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The questions of the one-value solvability of an inverse boundary value problem for a mixed type integro-differential equation with Caputo operators of different fractional orders and spectral parameters are considered.
Tursun K. Yuldashev, Erkinjon T. Karimov
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A double inverse problem for Fredholm integro-differential equation of elliptic type
In this paper the double inverse problem for partial differential equations is considered. The method of studying the one value solvability of the double inverse problem for a Fredholm integro-differential equation of elliptic type with degenerate kernel
Tursun K Yuldashev
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Efficient Numerical Solution of Coupled Axisymmetric Plasma Equilibrium and Eddy Current Problems
This paper presents an efficient numerical tool for solving the problem of transient nonlinear evolution of plasma equilibrium in presence of eddy currents.
Matteo Bonotto +5 more
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ABSTRACT The well‐posedness results for mild solutions to the fractional neutral stochastic differential system with Rosenblatt process with Hurst index Ĥ∈12,1$$ \hat{H}\in \left(\frac{1}{2},1\right) $$ is discussed in this article. To demonstrate the results, the concept of bounded integral contractors is combined with the stochastic result and ...
Dimplekumar N. Chalishajar +3 more
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This research investigates the theoretical foundations and computational implementation of the Double ZZ Transform (DZZT) for solving nonlinear integro-partial differential equations. By establishing the transform's existence theorem and core properties, this study provides a systematic approach to handling non-homogeneous models.
Djelloul Ziane +3 more
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Individual bird identification by modelling temporal structure in bioacoustic embeddings
Abstract Identifying individual animals from vocalizations is an emerging research area in computational bioacoustics. This non‐invasive approach reduces reliance on physical capture and tagging for wildlife monitoring. Recent advances in this area leverage deep learning and bioacoustic foundation models adapted from species‐level classifiers. However,
Jonathan Gallego +2 more
wiley +1 more source
On the anticrowding population dynamics taking into account a discrete set of offspring
A model of a population dynamics is solved numerically taking into account a discrete set of offsprings and the nonlinear (directed) diffusion. The model consists of a system of integro-partial differential equations subject to conditions of integral ...
Šarūnas Repšys, Vladas Skakauskas
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Reinforcement Learning for Jump‐Diffusions, With Financial Applications
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
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Stochastic Gradient Descent in High Dimensions for Multi‐Spiked Tensor PCA
ABSTRACT We study the high‐dimensional dynamics of online stochastic gradient descent (SGD) for the multi‐spiked tensor model. This multi‐index model arises from the tensor principal component analysis (PCA) problem with multiple spikes, where the goal is to estimate the unknown signal vectors within the N$N$‐dimensional unit sphere through maximum ...
Gérard Ben Arous +2 more
wiley +1 more source

