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Found 3 papers, 1 papers with code
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
Experimentally, TimeXer significantly improves time series forecasting with exogenous variables and achieves consistent state-of-the-art performance in twelve real-world forecasting benchmarks.
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
To emphasize temporal correlation modeling, this paper proposes TimeSiam as a simple but effective self-supervised pre-training framework for Time series based on Siamese networks.
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
By relating masked modeling to manifold learning, SimMTM proposes to recover masked time points by the weighted aggregation of multiple neighbors outside the manifold, which eases the reconstruction task by assembling ruined but complementary temporal variations from multiple masked series.
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