Bisection problems, in particular, focus on the nearly equal division of a graph and are closely linked to studies in spectral graph theory and approximation algorithms.

This letter proposes a class of modified continuous-time (CT) and discrete-time (DT) finite-time convergence (FTC) estimators based on the dynamic regressor extension and mixing (DREM) method, ...

To address the issue of GNSS signal failure, this article presents an enhanced vehicle self-positioning method based on factor graph optimization (FGO) and convolutional neural network (CNN)-long ...

From its connectivity and distance information, DCGCN captures the relationships among atoms through a dual-channel graph convolutional network. Furthermore, 1D convolutional layers are employed to ...

This repository contains a Python implementation of numerical root-finding methods for solving ( f(x) = 0 ). The methods include Bisection, Newton-Raphson, Fixed Point Iteration, False Position, ...

Learn the advantages and disadvantages of BFS and DFS for graph traversal, and how to decide which one to use based on your problem and graph.

Plots training/validation loss convergence (output/convergence_graph.png) Run inference and visualize predictions: python inference_visualize.py Generates predicted masks and comparison images in ...

We investigate the variational quantum eigensolver (VQE) for estimating the ground-state energy of the BeH2 molecule, emphasizing practical implementation and performance on current quantum hardware.