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Hansika Hewamalage
Hansika Hewamalage
Data Scientist | Adjunct Associate Lecturer, School of Computer Science and Engineering, UNSW
Verified email at unsw.edu.au
Title
Cited by
Cited by
Year
Recurrent neural networks for time series forecasting: Current status and future directions
H Hewamalage, C Bergmeir, K Bandara
International Journal of Forecasting, 2020
3822020
Sales demand forecast in e-commerce using a long short-term memory neural network methodology
K Bandara, P Shi, C Bergmeir, H Hewamalage, Q Tran, B Seaman
International conference on neural information processing, 462-474, 2019
1282019
LSTM-MSNet: Leveraging forecasts on sets of related time series with multiple seasonal patterns
K Bandara, C Bergmeir, H Hewamalage
IEEE transactions on neural networks and learning systems 32 (4), 1586-1599, 2020
732020
Improving the accuracy of global forecasting models using time series data augmentation
K Bandara, H Hewamalage, YH Liu, Y Kang, C Bergmeir
Pattern Recognition 120, 108148, 2021
472021
Global models for time series forecasting: A simulation study
H Hewamalage, C Bergmeir, K Bandara
Pattern Recognition 124, 108441, 2022
232022
Neuralprophet: Explainable forecasting at scale
O Triebe, H Hewamalage, P Pilyugina, N Laptev, C Bergmeir, ...
arXiv preprint arXiv:2111.15397, 2021
212021
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition
K Bandara, H Hewamalage, R Godahewa, P Gamakumara
International Journal of Forecasting 38 (4), 1400-1404, 2022
82022
Evaluation of feature-based object identification for augmented reality applications on mobile devices
B Hettige, H Hewamalage, C Rajapaksha, N Wajirasena, A Pemasiri, ...
2015 IEEE 10th International Conference on Industrial and Information …, 2015
72015
Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practices
H Hewamalage, K Ackermann, C Bergmeir
arXiv preprint arXiv:2203.10716, 2022
32022
Deep Learning Approaches for Long-Term Global Horizontal Irradiance Forecasting for Microgrids Planning
AA Medina-Santana, H Hewamalage, LE Cárdenas-Barrón
Designs 6 (5), 83, 2022
12022
A Look at the Evaluation Setup of the M5 Forecasting Competition
H Hewamalage, P Montero-Manso, C Bergmeir, RJ Hyndman
arXiv preprint arXiv:2108.03588, 2021
12021
Advancing Time Series Forecasting Techniques & Practices in a Big Data Environment
HP HEWAMALAGE
Monash University, 2022
2022
Global models for time series forecasting: A simulation study
H Hewamalage, C Bergmeir, K Bandara
40th International Symposium on Forecasting, 2020
2020
Recurrent Neural Networks for Time Series Forecasting: An Overview and Empirical Evaluations
H Hewamalage, C Bergmeir, K Bandara
39th International Symposium on Forecasting, Thessaloniki, Greece, 2019
2019
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Articles 1–14