IEEE

Topology-Aware Graph Neural Network-Based State Estimation for PMU-Unobservable Power Systems

Abstract: Traditional optimization-based techniques for time-synchronized state estimation (SE) often suffer from high online computational burden, limited phasor measurement unit (PMU) coverage, and ...
Learn With Jay on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
IEEE

Survey on Graph Neural Networks

Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures, allows ...
GitHub

An Efficient Implementation of Kolmogorov-Arnold Network

This repository contains an efficient implementation of Kolmogorov-Arnold Network (KAN). The original implementation of KAN is available here. The problem is in the sparsification which is claimed to ...