To identify and evaluate candidate materials, process engineers must analyze an enormous amount of data. Bulk properties like resistivity or thermal conductivity are a starting point, but these ...
Self-organizing maps, and the machine learning protocol involved in creating them, have been in use since the 1980s, Lawrence ...
Research shows how artificial intelligence is revolutionizing plastics manufacturing through material development and process ...
A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.
Organizations in today’s digital economy are constantly facing unprecedented pressure to innovate, accelerate decision-making ...
This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine ...
Pranav Prabhakar is an engineering leader with expertise in building scalable systems, deploying machine learning in ...
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Overparameterized neural networks: Feature learning precedes overfitting, research finds
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
SerpApi provides real-time structured access to public search engine results. Founded in 2017 by Julien Khaleghy, the company ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
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