Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the ...
Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...
In today's machine learning field, deep neural network models are becoming increasingly large and complex, posing significant challenges to traditional electronic computing hardware. To address this ...
Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
In May, more Americans watched television on streaming than on cable and network television combined, Nielsen said. It is the first time that has happened over a full month. By John Koblin The ...
Abstract: Dynamic activation functions usually gain remarkable improvements for neural networks. Dynamic activation functions depending on input features show better performance than the ...
This project implements a linear neural network to recognize digits from the MNIST dataset. MNIST (Modified National Institute of Standards and Technology) is a widely used dataset for training and ...
Abstract: The engineering of molecular programs capable of processing patterns of multi-input biomarkers holds great potential in applications ranging from in vitro diagnostics (e.g., viral detection, ...
The evaluation of the structural response statistics constitutes one of the principal tasks in engineering. However, in the tail region near structural failure, engineering structures behave highly ...
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