值得注意的是,在Weather数据集上,xLSTM-Mixer将MAE降低了2%(与xLSTMTime相比)和4.6%(与TimeMixer相比)。同样,在ETTm1数据集上,xLSTM-Mixer在MAE上优于TimeMixer 2.4%,并且与xLSTMTime相比具有强大的竞争优势。尽管在处理异常值方面,xLSTM-Mixer在Traffic和ETTh2数据集上的表现略逊一筹,但它仍然具有很强的竞争...
Time series data is prevalent across numerous fields, necessitating the development of robust and accurate forecasting models. Capturing patterns both within and between temporal and multivariate components is crucial for reliable predictions. We introduce xLSTM-Mixer, a model designed to effectively integr...