Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of Forecasting 38 (3), 705-871, 2022 | 598 | 2022 |
Probabilistic forecasting with temporal convolutional neural network Y Chen, Y Kang, Y Chen, Z Wang Neurocomputing 399, 491-501, 2020 | 309 | 2020 |
Visualising forecasting algorithm performance using time series instance spaces Y Kang, RJ Hyndman, K Smith-Miles International Journal of Forecasting 33 (2), 345-358, 2017 | 193 | 2017 |
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics Y Kang, RJ Hyndman, F Li Statistical Analysis and Data Mining: The ASA Data Science Journal 13 (4 …, 2020 | 134 | 2020 |
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 | 118 | 2021 |
Forecast combinations: an over 50-year review X Wang, RJ Hyndman, F Li, Y Kang International Journal of Forecasting, 2022 | 101 | 2022 |
tsfeatures: Time series feature extraction R Hyndman, Y Kang, P Montero-Manso, T Talagala, E Wang, Y Yang, ... R package version 1 (0), 2019 | 100* | 2019 |
Forecasting with time series imaging X Li, Y Kang, F Li Expert Systems with Applications 160, 113680, 2020 | 80 | 2020 |
Classes of structures in the stable atmospheric boundary layer Y Kang, D Belušić, K Smith‐Miles Quarterly Journal of the Royal Meteorological Society 141 (691), 2057-2069, 2015 | 49 | 2015 |
Detecting and classifying events in noisy time series Y Kang, D Belušić, K Smith-Miles Journal of the Atmospheric Sciences 71 (3), 1090-1104, 2014 | 45 | 2014 |
Distributed ARIMA models for ultra-long time series X Wang, Y Kang, RJ Hyndman, F Li International Journal of Forecasting 39 (3), 1163-1184, 2023 | 34 | 2023 |
Forecast with Forecasts: Diversity Matters Y Kang, W Cao, F Petropoulos, F Li European Journal of Operational Research, 2021 | 27 | 2021 |
FFORMPP: Feature-based forecast model performance prediction TS Talagala, F Li, Y Kang International Journal of Forecasting 38 (3), 920-943, 2022 | 26 | 2022 |
Exploring the representativeness of the M5 competition data E Theodorou, S Wang, Y Kang, E Spiliotis, S Makridakis, ... International Journal of Forecasting, 2021 | 22 | 2021 |
Déjà vu: A data-centric forecasting approach through time series cross-similarity Y Kang, E Spiliotis, F Petropoulos, N Athiniotis, F Li, V Assimakopoulos Journal of Business Research 132, 719-731, 2021 | 22 | 2021 |
Improving forecasting performance using covariate-dependent copula models F Li, Y Kang International Journal of Forecasting 34 (3), 456-476, 2018 | 21* | 2018 |
Large language models: Their success and impact S Makridakis, F Petropoulos, Y Kang Forecasting 5 (3), 536-549, 2023 | 19 | 2023 |
The uncertainty estimation of feature-based forecast combinations X Wang, Y Kang, F Petropoulos, F Li Journal of the Operational Research Society 73 (5), 979-993, 2022 | 17 | 2022 |
Improving forecasting by subsampling seasonal time series X Li, F Petropoulos, Y Kang International Journal of Production Research 61 (3), 976-992, 2023 | 14* | 2023 |
Bayesian forecast combination using time-varying features L Li, Y Kang, F Li International Journal of Forecasting 39 (3), 1287-1302, 2023 | 11 | 2023 |