IEEE

Uncertainty-Aware Graph Neural Networks: A Multihop Evidence Fusion Approach

Abstract: Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertainty of ...
GitHub

This repo describes python code and input data files for "Forecasting stock return distributions around the globe with quantile neural networks".

Inputs: describes all the raw inputs to run the code Code description: describes the python code and how to run it Code to figure mapping: provides mapping of figures in the paper to code used to ...
IEEE

Contra Harmonic Mean Labeling of Some Graphs and Python-Based Continuous-Time Neural Networks for Solving the Travelling Salesman Problem in Artificial Intelligence

Abstract: In this paper, we prove Contra Harmonic Mean Labeling for some star related graphs such as $\mathrm{K}_{1, \mathrm{n}}, S(\mathrm{K}_{1, \mathrm{n ...