Abstract: This paper addresses the problem of joint modeling for multi-source heterogeneous graph data in distributed environments by proposing a federated graph neural network classification ...

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 ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

This video is an overall package to understand L2 Regularization Neural Network and then implement it in Python from scratch. L2 Regularization neural network it a technique to overcome overfitting.

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...

A complete, professional neural network implementation built entirely from scratch using only NumPy for MNIST digit classification. This project achieves 98.06% test accuracy with a clean, ...

Transition metal complexes (TMCs) are of great scientific and practical interest for applications in catalysis, biological systems, photochemistry, and sustainability, with properties highly dependent ...