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02/02/2023
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
Time series analysis is widely used in extensive areas. Recently, to red...
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01/30/2023
Solving High-Dimensional PDEs with Latent Spectral Models
Deep models have achieved impressive progress in solving partial differe...
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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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02/13/2022
Flowformer: Linearizing Transformers with Conservation Flows
Transformers based on the attention mechanism have achieved impressive s...
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02/13/2022
Supported Policy Optimization for Offline Reinforcement Learning
Policy constraint methods to offline reinforcement learning (RL) typical...
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10/08/2021
ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning
Learning predictive models for unlabeled spatiotemporal data is challeng...
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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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06/24/2021
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
Extending the forecasting time is a critical demand for real application...
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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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03/03/2021
