Abstract: In this paper a novel approach for automatically configuring a k-nearest neighbors regressor for univariate time series forecasting is presented. The approach uses an ensemble consisting of ...

1 Department of Physiology, School of Basic Medicine, Kunming Medical University, Kunming, Yunnan, China 2 School of Public Health, Kunming Medical University, Kunming, Yunnan, China Objective: The ...

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Thank you for your interesting tutorial！ I would like to use the TabPFN-TS model to perform predictions on a multivariate time series dataset. The dataset contains one column of temporal information ...

I am interested in time series forecasting and I would like to use S4D as in example.py to run it in external repositories. How should the S4Model class in example.py be modified in order to correctly ...

Abstract: Univariate time series forecasting is pivotal in domains such as climate modeling, finance, and healthcare, where both short-term precision and long-term reliability are essential. This ...

In this study, we introduce a novel quantum counterpart to classical neurons, paving the way for quantum backpropagation neural networks that exhibit the potential for universal quantum computation in ...

When modeling sub-national mortality rates, it is important to incorporate any possible correlation among sub-populations to improve forecast accuracy. Moreover, forecasts at the sub-national level ...