Abstract: Time series data permeates our daily existence and has been recognized as of significant importance for many sectors, such as energy, transportation, telecommunication, and health care.
We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...
Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.
The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.
The official code for ["TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)"]. TEMPO is one of the very first open source Time Series Foundation Models for ...
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