Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...

Abstract: Learning Markov blankets (MBs) plays an important role in many machine learning tasks, such as causal Bayesian network structure learning, feature selection, and domain adaptation. Since ...

Abstract: Software testing is a crucial activity during software development and fault prediction models assist practitioners herein by providing an upfront identification of faulty software code by ...

Medicine has always operated as an “evidence based” field, meaning that it generally pursues experimentation to gather ...

Five students partnered with Dr. Ahmad Ghafarian, a UNG professor of computer science and cybersecurity, on the application ...

For two decades, the telecommunications industry has operated on a familiar premise: Build the pipe, push the data and scale the infrastructure. My previous writings explored how the convergence of ...

Applied physics is the study of physics for a practical purpose, as opposed to physics motived solely for an improved fundamental understanding. This includes technological advances such as the ...

July 2, 2026 A major breakthrough in quantum technology has turned magnons, tiny magnetic waves once considered too short-lived for practical use, into promising carriers of quantum information.

In the midst of epidemics such as COVID-19, therapeutic candidates are unlikely to be able to complete the usual multiyear clinical trial and regulatory approval process within the course of an ...

SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: Benchmarks of equation solver implementations ...

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