Results 51 to 60 of about 36,851 (159)

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance

open access: yesNaval Research Logistics (NRL), EarlyView.
ABSTRACT The rapid expansion of cross‐border e‐commerce (CBEC) has created significant opportunities for small‐ and medium‐sized sellers, yet financing remains a critical challenge due to their limited credit histories. Third‐party logistics (3PL)‐led supply chain finance (SCF) has emerged as a promising solution, leveraging in‐transit inventory as ...
Qingkai Zhang, L. Jeff Hong, Houmin Yan
wiley   +1 more source

Lipschitz geometry of operator spaces and Lipschitz-free operator spaces

open access: yesMathematische Annalen, 2022
arXiv admin note: text overlap with arXiv:1911 ...
Bruno M. Braga   +2 more
openaire   +2 more sources

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

open access: yesQuality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim   +3 more
wiley   +1 more source

Recursive Feasibility of Nonlinear Stochastic Model Predictive Control With Gaussian Process Dynamics

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf   +2 more
wiley   +1 more source

The approximation property for spaces of Lipschitz functions [PDF]

open access: yes, 2014
Let $\mathrm{Lip}_0(X)$ be the space of all Lipschitz scalar-valued functions on a pointed metric space $X$. We characterize the approximation property for $\mathrm{Lip}_0(X)$ with the bounded weak* topology using as tools the tensor product, the ...
Vargas, Antonio Jiménez
core  

Synthesizing Interacting Model‐Based Optimal Control and Model‐Free Learning Approaches for Nonlinear Systems

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we consider the optimal control problem for an unknown continuous‐time nonlinear system, and present a framework that integrates model‐based and model‐free methods to solve it. Each approach offers distinct advantages: model‐based techniques provide offline synthesis and data efficiency, while model‐free procedures excel at ...
Surabhi Athalye   +2 more
wiley   +1 more source

Multi‐Agent Reinforcement Learning Driven Dynamic Resource Optimisation in Healthcare Transportation Networks

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency module to capture complex spatiotemporal relationships in healthcare demand and resource allocation patterns, combined with centralised ...
Jianhui Lv   +3 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier   +5 more
wiley   +1 more source

On Metric Choice in Dimension Reduction for Fréchet Regression

open access: yesInternational Statistical Review, EarlyView.
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale   +3 more
wiley   +1 more source

A Comparative Review of Specification Tests for Diffusion Models

open access: yesInternational Statistical Review, EarlyView.
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez   +3 more
wiley   +1 more source

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