21 citations · 43 across the 8 of their papers we have counts for
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cs.LG2025
PFformer: A Position-Free Transformer Variant for Extreme-Adaptive Multivariate Time Series Forecasting
Yanhong Li, David C. Anastasiu
Multivariate time series (MTS) forecasting is vital in fields like weather, energy, and finance. However, despite deep learning advancements, traditional Transformer-based models o…
cs.LG2023★ 1 cited
Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting
Yanhong Li, Jack Xu, David C. Anastasiu
In the hydrology field, time series forecasting is crucial for efficient water resource management, improving flood and drought control and increasing the safety and quality of lif…
cs.LG2022★ 21 cited
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks
Yanhong Li, Jack Xu, David C. Anastasiu
Forecasting time series with extreme events has been a challenging and prevalent research topic, especially when the time series data are affected by complicated uncertain factors,…