Learn how to understand and compute line integrals in vector fields using both Python and traditional paper methods! This video walks you step by step through the concepts of line integrals, ...

Abstract: Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have ...

Every time a language model like GPT-4, Claude or Mistral generates a sentence, it does something deceptively simple: It picks one word at a time. This word-by-word approach is what gives ...

Objective: This study aimed to develop depression incidence forecasting models and compare the performance of autoregressive integrated moving average (ARIMA) and vector-ARIMA (VARIMA) and temporal ...

Abstract: As an efficient recurrent neural network (RNN), reservoir computing (RC) has achieved various applications in time-series forecasting. Nevertheless, a poorly explained phenomenon remains as ...

ABSTRACT: To improve the efficiency of air quality analysis and the accuracy of predictions, this paper proposes a composite method based on Vector Autoregressive (VAR) and Random Forest (RF) models.

Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at handling large datasets and are very strong at ...

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