Euclid preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events

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Simultaneous Quantification of Multiple Drugs by Machine Learning on Electrochemical Sensors

Sandro Carrara, Lin Du, Tatsunori Matsumoto

Electrochemical devices and systems are significant for the development of therapeutic drug monitoring (TDM) and personalized therapy. However, electrochemical sensors are usually not that much selective. Therefore, innovative machine learning (ML) approac ...

Institute of Electrical and Electronics Engineers Inc.2024

Considering the incidence rate of RR Lyrae stars with non-radial modes

Henryka Ewa Netzel

Context. Over recent years, additional low-amplitude non-radial modes have been detected in many first-overtone RR Lyrae stars. These non-radial modes form a characteristic period ratio with the dominant first overtone of around 0.61. The incidence rate of ...

EDP SCIENCES S A2024

Efficient Recursive Data-enabled Predictive Control

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

In the field of model predictive control, Dataenabled Predictive Control (DeePC) offers direct predictive control, bypassing traditional modeling. However, challenges emerge with increased computational demand due to recursive data updates. This paper intr ...

IEEE2024

A PAC-Bayesian Framework for Optimal Control with Stability Guarantees

Mahrokh Ghoddousiboroujeni, Giancarlo Ferrari Trecate, Clara Lucía Galimberti

Stochastic Nonlinear Optimal Control (SNOC) involves minimizing a cost function that averages out the random uncertainties affecting the dynamics of nonlinear systems. For tractability reasons, this problem is typically addressed by minimizing an empirical ...

IEEE2024