Google releases TimesFM-3, a 330M parameter zero-shot foundation model for multivariate time series forecasting in one ...
ABSTRACT: Pyrethrum (Chrysanthemum cinerariaefolium L.) is an industrial crop with complex morphology and diverse physico-mechanical properties that jeopardize the optimal design of precision ...
ABSTRACT: This study develops and empirically calibrates the Community-Social Licence-Insurance Equilibrium (CoSLIE) Model, a dynamic, multi-theoretic framework that reconceptualises ...
Abstract: Multivariate time series forecasting estimates future development by capturing variable relationships and constructing temporal regular, which is widely used in many scenarios, including ...
Previous studies that focused on univariate correlations between neuroanatomy and cognition in schizophrenia identified some inconsistent findings. Moreover, antipsychotic medication may impact the ...
This repository contains data and code to compute models for correlation matrices with a user-defined graphical structure. The graphical structure makes correlation matrices interpretable and avoids ...
Uncertainty quantification is crucial to decision-making. A prominent example is probabilistic forecasting in numerical weather prediction. The dominant approach to representing uncertainty in weather ...
Transformer has become the basic model that adheres to the scaling rule after achieving great success in natural language processing and computer vision. Time series forecasting is seeing the ...
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