What if We Enrich day ahead Solar Time Series Forecasting with Temporal Context Supplementary material

For both15 modalities, essential information such as geographic coordinates, elevation, and precise time-stamps16 is available. In this section, we provide a comprehensive explanation of the encoding process for each17 feature and conclude by presenting the hyperparameters of the model.18 For each time point, we have access to the following time19 features: The year, the month, the day, the hour and the minute at which the measurement was made.20 We use a cyclical embedding to encode these time features discarding the year. For a time feature x,21 its corresponding embedding can be expressed as:22 sin 2πx ω(x),cos 2πx ω(x) (1) Submitted to 37th Conference on Neural Information Processing Systems (NeurIPS 2023).