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05/30/2023
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
Real-world time series is characterized by intrinsic non-stationarity th...
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02/02/2023
CLIPood: Generalizing CLIP to Out-of-Distributions
Out-of-distribution (OOD) generalization, where the model needs to handl...
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10/05/2022
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
Time series analysis is of immense importance in extensive applications,...
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05/28/2022
Non-stationary Transformers: Rethinking the Stationarity in Time Series Forecasting
Transformers have shown great power in time series forecasting due to th...
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10/14/2021
Omni-Training for Data-Efficient Deep Learning
Learning a generalizable deep model from a few examples in a short time ...
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10/06/2021
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
Unsupervisedly detecting anomaly points in time series is challenging, w...
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03/17/2021
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning
The predictive learning of spatiotemporal sequences aims to generate fut...
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12/08/2019
Less Confusion More Transferable: Minimum Class Confusion for Versatile Domain Adaptation
Domain Adaptation (DA) transfers a learning model from a labeled source ...
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10/27/2017
