BACKGROUND: Forecasts for the future prevalence of cardiovascular disease and stroke are crucial to guide efforts to improve health outcomes across the life course for women. METHODS: Using historical ...
Robert Stammer, CFA, is the former director of investor engagement at CFA Institute and writes on thought leadership in the investment management industry. Charlene Rhinehart is a CPA , CFE, chair of ...
With Elon Musk’s dealings with Donald Trump and late night rants on X, there’s so much noise around Tesla that it’s easy to forget that it makes cars. But it does – and the Tesla Model 3 is the most ...
A biophysical model is a simulation of a biological system using mathematical formalizations of the physical properties of that system. Such models can be used to predict the influence of biological ...
Abstract: Time series forecasting plays a vital role in various fields such as energy forecasting and transportation planning. Although Transformer-based models have made remarkable progress in time ...
Abstract: Industrial time series prediction (ITSP) is critical to the predictive maintenance system of modern industry. However, time-varying conditions and complex industrial processes cause the ...
Large Language Models (LLMs) have emerged as powerful tools for interpreting multimodal data (e.g., images, audio, text), often surpassing specialized models. In medicine, they hold particular promise ...
The code is implemented in Python using the PyTorch framework. DACAD is a PyTorch-based framework for unsupervised domain adaptation in multivariate time series anomaly detection that hsa been ...
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