2 citations · 2 across the 2 of their papers we have counts for
3 papers
Sequential Learning-Based Physics-Informed Neural Network Modeling for Parameter Estimation on a Power Converter
Samuela Rokocakau, Panagiotis Kakosimos, Giulia Tresca +1
A staged physics-informed neural network (PINN) is proposed for identifying the inductance, capacitance and parasitic resistances of a DC buck converter from time-domain data. Grad…
System Identification Using Kolmogorov-Arnold Networks: A Case Study on Buck Converters
Nart Gashi, Panagiotis Kakosimos, George Papafotiou
Kolmogorov-Arnold Networks (KANs) are emerging as a powerful framework for interpretable and efficient system identification in dynamic systems. By leveraging the Kolmogorov-Arnold…
An Adaptive ML Framework for Power Converter Monitoring via Federated Transfer Learning
Panagiotis Kakosimos, Alireza Nemat Saberi, Luca Peretti
This study explores alternative framework configurations for adapting thermal machine learning (ML) models for power converters by combining transfer learning (TL) and federated le…