Results 111 to 120 of about 4,564 (243)
Mathematical Finance, EarlyView.ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici +3 more
wiley +1 more source
Dam Management in the Era of Climate Change
Mathematical Finance, EarlyView.ABSTRACT Climate change has a dramatic impact, particularly by concentrating rainfall into a few short periods, interspersed with long dry spells. In this context, the role of dams is crucial. We consider the optimal control of a dam, where the water level must neither exceed a designated safety threshold nor fall below a minimum level to ensure ...
Cristina Di Girolami +3 more
wiley +1 more source
Heat kernel estimates for Markov processes with blowing-up jump kernels
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Cho, Soobin +3 more
openaire +2 more sources
Frequency‐dependent contraction rates for the Bayesian method to the inverse source problem
Transactions of the London Mathematical Society, Volume 13, Issue 1, December 2026.Abstract This paper addresses an inverse source problem for acoustic waves in a range of frequencies. Our study has two main goals. First, although the problem is severely ill‐posed with a logarithmic stability estimate, we demonstrate, through careful analysis of the forward map's singular values, that increasing the frequency range enhances stability,
Pu‐Zhao Kow, Jenn‐Nan Wang
wiley +1 more source
Kernel estimation of the transition density in bifurcating Markov chains
Journal of Statistical Planning and InferenceWe study the kernel estimator of the transition density of bifurcating Markov chains. Under some ergodic and regularity properties, we prove that this estimator is consistent and asymptotically normal. Next, in the numerical studies, we propose two data-driven methods to choose the bandwidth parameters.
openaire +5 more sources
Stochastic Gradient Descent in High Dimensions for Multi‐Spiked Tensor PCA
Communications on Pure and Applied Mathematics, Volume 79, Issue 10, Page 2291-2369, October 2026.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
Age Replacement for Balanced Systems Under Mission Durations
Quality and Reliability Engineering International, Volume 42, Issue 6, Page 3369-3384, October 2026.ABSTRACT With advances in technology, systems such as Unmanned Aerial Vehicles (UAV) and planetary landing vehicles whose operation requires maintaining balance across sectors have attracted increasing attention within the balanced systems literature.
Ferhan BAŞ KAMAN
wiley +1 more source
Ecology of Freshwater Fish, Volume 35, Issue 4, October 2026.ABSTRACT Temperate lake ecosystems undergo seasonal shifts that disproportionately alter the availability of suitable habitat for fishes of different thermal guilds. While many studies have investigated fish habitat use patterns, few have estimated the degree to which fish species overlap in space across seasons from a three‐dimensional perspective ...
Ian A. Richter +3 more
wiley +1 more source
GEMA: Graph Embeddings for Multi‐Agent Coordination
AI Magazine, Volume 47, Issue 3, Fall 2026.Abstract Many cooperative multi‐agent tasks are naturally defined by graph‐structured objectives, where agents must collectively reach, for example, a desired relational configuration or satisfy a set of constraints. These objectives often encode spatial arrangements, inter‐agent relations, or constraints that can be formalized as target graphs ...
Alessandro Amato +3 more
wiley +1 more source
Deep Spatially Varying Coefficient Model for Interpolation of Non‐Stationary Meteorological Data
Environmetrics, Volume 37, Issue 6, September 2026.ABSTRACT In spatial statistics, the spatially varying coefficient model (SVCM) is widely applied in the analysis and interpolation of non‐stationary spatial data. By incorporating spatially varying coefficients, the model can capture spatial heterogeneity and provide an attractive interpretation of response‐covariate associations.
Tong Wu, Nan Chen, Zhi‐Sheng Ye
wiley +1 more source