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Found 6 papers, 4 papers with code
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
For the state-of-the-art (SOTA) model, the MSE is reduced by $33. 3\%$.
WeatherGNN: Exploiting Complicated Relationships in Numerical Weather Prediction Bias Correction
In addition, the interactions between weather factors are further complicated by the spatial dependencies between regions, which are influenced by varied terrain and atmospheric motions.
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling
Online updating of time series forecasting models aims to address the concept drifting problem by efficiently updating forecasting models based on streaming data.
Transformers in Time Series: A Survey
From the perspective of network structure, we summarize the adaptations and modifications that have been made to Transformers in order to accommodate the challenges in time series analysis.
Learning from Multiple Time Series: A Deep Disentangled Approach to Diversified Time Series Forecasting
Time series forecasting is a significant problem in many applications, e. g., financial predictions and business optimization.
Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting
Traffic forecasting is of great importance to transportation management and public safety, and very challenging due to the complicated spatial-temporal dependency and essential uncertainty brought about by the road network and traffic conditions.
