activity
20202023
most citedComparison of Recurrent Neural Network Architectures for Wildfire Spread Modelling

15 citations · 52 across the 31 of their papers we have counts for

collaborators

32 papers

q-fin.PM2023★ 5 cited

Machine Learning for Socially Responsible Portfolio Optimisation

Taeisha Nundlall, Terence L Van Zyl

Socially responsible investors build investment portfolios intending to incite social and environmental advancement alongside a financial return. Although Mean-Variance (MV) models…

cs.LG2023

A Learnheuristic Approach to A Constrained Multi-Objective Portfolio Optimisation Problem

Sonia Bullah, Terence L. van Zyl

Multi-objective portfolio optimisation is a critical problem researched across various fields of study as it achieves the objective of maximising the expected return while minimisi…

cs.LG2023★ 1 cited

Late Meta-learning Fusion Using Representation Learning for Time Series Forecasting

Terence L. van Zyl

Meta-learning, decision fusion, hybrid models, and representation learning are topics of investigation with significant traction in time-series forecasting research. Of these two s…

cs.LG2022★ 1 cited

Volatility forecasting using Deep Learning and sentiment analysis

V Ncume, T. L van Zyl, A Paskaramoorthy

Several studies have shown that deep learning models can provide more accurate volatility forecasts than the traditional methods used within this domain. This paper presents a comp…

cs.LG2022

Towards a methodology for addressing missingness in datasets, with an application to demographic health datasets

Gift Khangamwa, Terence L. van Zyl, Clint J. van Alten

Missing data is a common concern in health datasets, and its impact on good decision-making processes is well documented. Our study's contribution is a methodology for tackling mis…

cs.CL2022

Improving Cause-of-Death Classification from Verbal Autopsy Reports

Thokozile Manaka, Terence van Zyl, Deepak Kar

In many lower-and-middle income countries including South Africa, data access in health facilities is restricted due to patient privacy and confidentiality policies. Further, since…