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Time Series Forecasting with Graph Transformers
Time series forecasting is a cornerstone in modern business analytics, whether it is concerned with anticipating market trends, user behavior, optimizing resource allocation, or planning for future growth. This blog post will dive into forecasting on graph structured entities, e.g., as obtained from a relational database, utilizing not only the individual time series as signal but also related information.
Time series forecasting is a cornerstone in modern business analytics, whether it is concerned with anticipating market trends, user behavior, optimizing resource allocation, or planning for future growth. Forecasting is the process of making predictions about future events based on historical data and current observations, requiring detecting patterns, trends, and seasonal variations. Data flow shown for one entity.The forecasting head unifies information from the graph, the past time series, temporal frequency encodings and calendar features.
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