Related Work¶
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James Bergstra, Yoshua Bengio (2012). Random Search for Hyper-Parameter Optimization. https://www.jmlr.org/papers/volume13/bergstra12a/bergstra12a.pdf
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Jan Gasthaus (2016). Non-parametric time series forecaster. Technical report, Amazon, 2016.
Rob J. Hyndman, Anne B. Koehler, Ralph D. Snyder, and Simone Grose (2002). A State Space Framework for Automatic Forecasting using Exponential Smoothing Methods. https://doi.org/10.1016/S0169-2070(01)00110-8
Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski (2018). Deep State Space Models for Time Series Forecasting. https://papers.nips.cc/paper/2018/hash/5cf68969fb67aa6082363a6d4e6468e2-Abstract.html
Suman Ravuri et al. (2021). Skilful precipitation nowcasting using deep generative models of radar. https://www.nature.com/articles/s41586-021-03854-z
Rafael de Rezende, Katharina Egert, Ignacio Marin, Guilherme Thompson (2021). A White-boxed ISSM Approach to Estimate Uncertainty Distributions of Walmart Sales. https://arxiv.org/abs/2111.14721
Matthias Seeger, David Salinas, Valentin Flunkert (2016). Bayesian Intermittent Demand Forecasting for Large Inventories. https://papers.nips.cc/paper/2016/hash/03255088ed63354a54e0e5ed957e9008-Abstract.html
Matthias Seeger, Syama Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert (2017). Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. https://arxiv.org/abs/1709.07638
Oleksandr Shchur, Abdul Fatir Ansari, Caner Turkmen, Lorenzo Stella, Nick Erickson, Pablo Guerron, Michael Bohlke-Schneider, Yuyang Wang (2025). fev-bench: A Realistic Benchmark for Time Series Forecasting. https://arxiv.org/abs/2509.26468
Winters (1960). Forecasting Sales by Exponentially Weighted Moving Averages. https://doi.org/10.1287/mnsc.6.3.324