A Primer on Temporal Graph Learning

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Rahman, Aniq Ur, Coon, Justin P.
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914635583586304
author Rahman, Aniq Ur
Coon, Justin P.
author_facet Rahman, Aniq Ur
Coon, Justin P.
contents This document aims to familiarize readers with temporal graph learning (TGL) through a concept-first approach. We have systematically presented vital concepts essential for understanding the workings of a TGL framework. In addition to qualitative explanations, we have incorporated mathematical formulations where applicable, enhancing the clarity of the text. Since TGL involves temporal and spatial learning, we introduce relevant learning architectures ranging from recurrent and convolutional neural networks to transformers and graph neural networks. We also discuss classical time series forecasting methods to inspire interpretable learning solutions for TGL.
format Preprint
id arxiv_https___arxiv_org_abs_2401_03988
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Primer on Temporal Graph Learning
Rahman, Aniq Ur
Coon, Justin P.
Machine Learning
Artificial Intelligence
Discrete Mathematics
Social and Information Networks
Signal Processing
This document aims to familiarize readers with temporal graph learning (TGL) through a concept-first approach. We have systematically presented vital concepts essential for understanding the workings of a TGL framework. In addition to qualitative explanations, we have incorporated mathematical formulations where applicable, enhancing the clarity of the text. Since TGL involves temporal and spatial learning, we introduce relevant learning architectures ranging from recurrent and convolutional neural networks to transformers and graph neural networks. We also discuss classical time series forecasting methods to inspire interpretable learning solutions for TGL.
title A Primer on Temporal Graph Learning
topic Machine Learning
Artificial Intelligence
Discrete Mathematics
Social and Information Networks
Signal Processing
url https://arxiv.org/abs/2401.03988