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引用“”的文章Statistical and Machine Learning forecasting methods: Concerns and ways forward

标题/作者	年份
The M4 Competition: 100,000 time series and 61 forecasting methods S Makridakis, E Spiliotis, V Assimakopoulos International Journal of Forecasting 36 (1), 54-74	2020
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting BN Oreshkin, D Carpov, N Chapados, Y Bengio arXiv preprint arXiv:1905.10437	2019
Time-series forecasting with deep learning: a survey B Lim, S Zohren Philosophical Transactions of the Royal Society A 379 (2194), 20200209	2021
The M4 Competition: Results, findings, conclusion and way forward S Makridakis, E Spiliotis, V Assimakopoulos International Journal of Forecasting 34 (4), 802-808	2018
Recurrent neural networks for time series forecasting: Current status and future directions H Hewamalage, C Bergmeir, K Bandara International Journal of Forecasting 37 (1), 388-427	2021
A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting S Smyl International Journal of Forecasting 36 (1), 75-85	2020
COVID-19 future forecasting using supervised machine learning models F Rustam, AA Reshi, A Mehmood, S Ullah, BW On, W Aslam, GS Choi IEEE access 8, 101489-101499	2020
Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology A Botchkarev arXiv preprint arXiv:1809.03006	2018
Interpretable machine learning–a brief history, state-of-the-art and challenges C Molnar, G Casalicchio, B Bischl Joint European conference on machine learning and knowledge discovery in …	2020
Applications of deep learning in stock market prediction: recent progress W Jiang Expert Systems with Applications 184, 115537	2021
A new typology design of performance metrics to measure errors in machine learning regression algorithms A Botchkarev Interdisciplinary Journal of Information, Knowledge, and Management 14, 045-076	2019
Big-data science in porous materials: materials genomics and machine learning KM Jablonka, D Ongari, SM Moosavi, B Smit Chemical reviews 120 (16), 8066-8129	2020
Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of Forecasting 38 (3), 705-871	2022
M5 accuracy competition: Results, findings, and conclusions S Makridakis, E Spiliotis, V Assimakopoulos International Journal of Forecasting 38 (4), 1346-1364	2022
Forecasting inflation in a data-rich environment: the benefits of machine learning methods MC Medeiros, GFR Vasconcelos, Á Veiga, E Zilberman Journal of Business & Economic Statistics 39 (1), 98-119	2021
Probabilistic forecasting with temporal convolutional neural network Y Chen, Y Kang, Y Chen, Z Wang Neurocomputing 399, 491-501	2020
sktime: A unified interface for machine learning with time series M Löning, A Bagnall, S Ganesh, V Kazakov, J Lines, FJ Király arXiv preprint arXiv:1909.07872	2019
Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review MS Mirnaghi, F Haghighat Energy and Buildings 229, 110492	2020
Anomaly detection in univariate time-series: A survey on the state-of-the-art M Braei, S Wagner arXiv preprint arXiv:2004.00433	2020
A troubling analysis of reproducibility and progress in recommender systems research M Ferrari Dacrema, S Boglio, P Cremonesi, D Jannach ACM Transactions on Information Systems (TOIS) 39 (2), 1-49	2021

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