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A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data
The widespread deployment of wireless and mobile devices results in a proliferation of spatio-temporal data that is used in applications, e. g., traffic prediction, human mobility mining, and air quality prediction, where spatio-temporal prediction is often essential to enable safety, predictability, or reliability.
A Pattern Discovery Approach to Multivariate Time Series Forecasting
To capture the temporal and multivariate correlations among subsequences, we design a pattern discovery model, that constructs correlations via diverse pattern functions.
Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting
Long sequence time-series forecasting (LSTF) has become increasingly popular for its wide range of applications.
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