Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
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 ...
Neel Somani, a researcher specializing in mathematics, computer science, and business, has long explored the intersection ...
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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, ...
This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
Our era is defined by a constant flow of information. Data from smartphones, wearables and environmental sensors, connected to sharing and analysis platforms, accompany us daily, creating a digital ...
Unlike other industries, healthcare generates not only numerical and categorical data but also large volumes of unstructured ...
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