Results 81 to 90 of about 33,788 (311)
Asymptotic Convergence of Soft-Constrained Neural Networks for Density Estimation
Mathematics, 2020 A soft-constrained neural network for density estimation (SC-NN-4pdf) has recently been introduced to tackle the issues arising from the application of neural networks to density estimation problems (in particular, the satisfaction of the second ...
Edmondo Trentin
doaj +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
An Alternative Asymptotic Analysis of Residual-Based Statistics [PDF]
This paper presents an alternative method to derive the limiting distribution of residual-based statistics. Our method does not impose an explicit assumption of (asymptotic) smoothness of the statistic of interest with respect to the model's parameters ...
Bas J.M. Werker, Elena Andreou
core
Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping
Advanced Intelligent Systems, EarlyView.This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler +5 more
wiley +1 more source
Regression Asymptotics Using Martingale Convergence Methods [PDF]
Weak convergence of partial sums and multilinear forms in independent random variables and linear processes to stochastic integrals now plays a major role in nonstationary time series and has been central to the development of unit root econometrics. The
Peter C.B. Phillips, Rustam Ibragimov
core
Advanced Intelligent Systems, EarlyView.A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
Convergence and asymptotic variance of bootstrapped finite-time ruin probabilities with partly shifted risk processes. [PDF]
The classical risk model is considered and a sensitivity analysis of finite-time ruin probabilities is carried out. We prove the weak convergence of a sequence of empirical finite-time ruin probabilities.
Stéphane Loisel +2 more
core
Abstract and Applied Analysis, 2014 We give some improved convergence results about the smoothing-regularization approach to mathematical programs with vanishing constraints (MPVC for short), which is proposed in Achtziger et al. (2013).
Qingjie Hu +3 more
doaj +1 more source
On the Asymptotic Convergence of Subgraph Generated Models
IEEE Transactions on Network Science and EngineeringWe study a family of random graph models - termed subgraph generated models (SUGMs) - initially developed by Chandrasekhar and Jackson in which higher-order structures are explicitly included in the network formation process. We use matrix concentration inequalities to show convergence of the adjacency matrix of networks realized from such SUGMs to the
Xinchen Xu, Francesca Parise
openaire +2 more sources
Design Optimization of Soft Fabric Pneumatic Actuators
Advanced Intelligent Systems, EarlyView.This study presents a systematic optimization framework for elongating and bending fabric‐based soft pneumatic actuators. After a preliminary design‐space reduction, the framework minimizes energy consumption under mechanical performance constraints by integrating validated finite element modeling with statistical surrogate models. Optimal designs were
Grigorios M. Chatziathanasiou +2 more
wiley +1 more source