New Machine
Research on "new machines" broadly encompasses the development and application of machine learning across diverse fields, aiming to improve efficiency, accuracy, and decision-making. Current efforts focus on refining model architectures like convolutional neural networks, gradient boosting machines, and transformers for tasks ranging from image and signal processing to complex prediction and control problems. This research is significant because it drives advancements in various sectors, including healthcare, energy, manufacturing, and transportation, by enabling automated processes, improved diagnostics, and more efficient resource allocation.
Papers
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A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations
Andreas Windisch, Thomas Gallien, Christopher Schwarzlmueller
A machine learning analysis of the relationship between some underlying medical conditions and COVID-19 susceptibility
Mostafa Rezapour, Colin A. Varady
December 22, 2021
December 20, 2021
December 16, 2021
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December 13, 2021
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December 3, 2021