The article presents a novel method for time series forecasting, the Sparse Vector Quantized FFN-Free Transformer (Sparse-VQ). This approach leverages sparse vector quantization and Reverse Instance Normalization to reduce noise…
Continue readingThis study presents a new ensemble approach for feature selection in time series forecasting, particularly in non-stationary and limited sample scenarios. The approach utilizes a hierarchical structure to exploit feature…
Continue readingThe research introduces a novel LiDAR perception task of Occupancy Completion and Forecasting (OCF) in the field of autonomous driving. This task merges scene completion and forecasting into a unified…
Continue readingThe article discusses Onlineensembling Network (OneNet), a new approach to time series forecasting models to address the concept drift problem. OneNet updates two models focusing on time dimension dependency and…
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