most citedA Distance Correlation-Based Approach to Characterize the Effectiveness of Recurrent Neural Networks for Time Series Forecasting

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cs.LG2025

Online Kernel Dynamic Mode Decomposition for Streaming Time Series Forecasting with Adaptive Windowing

Christopher Salazar, Krithika Manohar, Ashis G. Banerjee

Real-time forecasting from streaming data poses critical challenges: handling non-stationary dynamics, operating under strict computational limits, and adapting rapidly without cat…

cs.LG2023★ 1 cited

A Distance Correlation-Based Approach to Characterize the Effectiveness of Recurrent Neural Networks for Time Series Forecasting

Christopher Salazar, Ashis G. Banerjee

Time series forecasting has received a lot of attention, with recurrent neural networks (RNNs) being one of the widely used models due to their ability to handle sequential data. P…