Resource Allocation Design for Next-Generation Multiple Access: A Tutorial Overview
Multiple access is the cornerstone technology for each generation of wireless cellular
networks, which fundamentally determines the method of radio resource sharing and …
networks, which fundamentally determines the method of radio resource sharing and …
Multi-fidelity neural optimization machine for Digital Twins
Abstract Digital Twins (DTs) are widely used for design, manufacturing, prognostics, and
decision support for operations. One critical challenge in optimizing DTs usually involves …
decision support for operations. One critical challenge in optimizing DTs usually involves …
Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
T Mu, P Liatsis, D Kyritsis - Advances in Neural …, 2024 - proceedings.neurips.cc
When deploying machine learning estimators in science and engineering (SAE) domains, it
is critical to avoid failed estimations that can have disastrous consequences, eg, in aero …
is critical to avoid failed estimations that can have disastrous consequences, eg, in aero …
Physics-driven ML-based modelling for correcting inverse estimation
When deploying machine learning estimators in science and engineering (SAE) domains, it
is critical to avoid failed estimations that can have disastrous consequences, eg, in aero …
is critical to avoid failed estimations that can have disastrous consequences, eg, in aero …
Node classification in networks via simplicial interactions
In the node classification task, it is intuitively understood that densely connected nodes tend
to exhibit similar attributes. However, it is crucial to first define what constitutes a dense …
to exhibit similar attributes. However, it is crucial to first define what constitutes a dense …
Physics-Driven AI Correction in Laser Absorption Sensing Quantification
Laser absorption spectroscopy (LAS) quantification is a popular tool used in measuring
temperature and concentration of gases. It has low error tolerance, whereas current ML …
temperature and concentration of gases. It has low error tolerance, whereas current ML …
EEE, Remediating the failure of machine learning models via a network-based optimization patch
A network-based optimization approach, EEE, is proposed for the purpose of providing
validation-viable state estimations to remediate the failure of pretrained models. To improve …
validation-viable state estimations to remediate the failure of pretrained models. To improve …
Neural Network-based Genetic Algorithm for Autonomous Boat Pathfinding
N Hamid, W Dharmawan… - 2023 IEEE 6th International …, 2023 - ieeexplore.ieee.org
Genetic algorithms become widely used in various optimization as a nature-inspired
algorithm. This biological-based algorithm includes three genetic operators: selection …
algorithm. This biological-based algorithm includes three genetic operators: selection …
ОПТИМІЗАЦІЯ АЛГОРИТМУ ВИЗНАЧЕННЯ КООРДИНАТ ДЖЕРЕЛА АКУСТИЧНОГО СИГНАЛУ ЗА КРИТЕРІЄМ МІНІМУМУ ПОХИБКИ
СІ Артемук, ІП Микитин - Збірник наукових праць Одеської …, 2023 - odatrya.org.ua
Анотація В даній роботі проведено дослідження зміни похибки визначення координат
джерела акустичного сигналу в залежності від різних параметрів розроблених …
джерела акустичного сигналу в залежності від різних параметрів розроблених …