Not all frequencies are created equal: towards a dynamic fusion of frequencies in time-series forecasting
X Zhang, S Zhao, Z Song, H Guo, J Zhang… - Proceedings of the …, 2024 - dl.acm.org
Long-term time series forecasting is a long-standing challenge in various applications. A
central issue in time series forecasting is that methods should expressively capture long …
central issue in time series forecasting is that methods should expressively capture long …
Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
Long-term urban mobility predictions play a crucial role in the effective management of
urban facilities and services. Conventionally, urban mobility data has been structured as …
urban facilities and services. Conventionally, urban mobility data has been structured as …
Multi-view Self-Supervised Contrastive Learning for Multivariate Time Series
Y Wu, X Meng, Y He, J Zhang, H Zhang… - Proceedings of the …, 2024 - dl.acm.org
Learning semantic-rich representations from unlabeled time series data with intricate
dynamics is a notable challenge. Traditional contrastive learning techniques predominantly …
dynamics is a notable challenge. Traditional contrastive learning techniques predominantly …
Rethinking Urban Mobility Prediction: A Multivariate Time Series Forecasting Approach
Long-term urban mobility predictions play a crucial role in the effective management of
urban facilities and services. Conventionally, urban mobility data has been structured as …
urban facilities and services. Conventionally, urban mobility data has been structured as …
Multi-scale hierarchical model for long-term time series forecasting
J Xu, LJ Zhang, DC Zhao, GL Ji, PH Li - Intelligent Data Analysis - content.iospress.com
Long-term time series forecasting (LTSF) has become an urgent requirement in many
applications, such as wind power supply planning. This is a highly challenging task because …
applications, such as wind power supply planning. This is a highly challenging task because …