A unified moment tensor potential for silicon, oxygen, and silica Karim Zongo Hao Sun Laurent Karim Béland npj Computational Materials(2024) Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning ...
Machine learning brings added value to the modeling of dynamics at the stand or individual tree level based on data from permanent plots. The objective of this study is to explore the potential of machine learning for modeling growth dynamics in uneven-aged forests at the diameter class ...
Fig. 1: Schematic illustrations of carbon-growth-on-metal machine-learning potential (CGM-MLP) generated by active learning on-the-fly during hybrid molecular dynamics and time-stamped force-biased Monte Carlo (MD/tfMC) simulations. a The initial training dataset includes representative carbon structu...
Machine learning apps save businesses money by streamlining inventory management and making production more efficient. They’re good at spotting potential equipment breakdowns before they happen. Machine learning apps can predict failure with a 92% accuracy rate, thanks to sensors attached to the equipme...
The increased awareness for business productivity, supplemented with competently designed machine learning solutions offered by vendors present in the APAC region, has led APAC to become a highly potential market. The major issue faced by most of the organizations while incorporating machine learning in...
A curated list of awesome responsible machine learning resources. - jphall663/awesome-machine-learning-interpretability
In the 21st century, data is the new oil, and machine learning is the engine that powers this data-driven world. It is a critical technology in today's digital age, and its importance cannot be overstated. This is reflected in the industry's projected growth, with the US Bureau of Labor...
Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima Gang Li, Kersten S. Rabe, Jens Nielsen, Martin K. M. Engqvist. ACS Synthetic Biology, May 2019 [10.1021/acssynbio.9b00099] mGPfusion: predicting protein stability changes with Gaussian process kernel...
According toHelomicsresearch, the global AI industry is anticipated to expand to $20 billion by 2025. It’s not just AI that presents growth possibilities; machine learning has the potential to disrupt long-standing industries as well. According to Gartner, the field of artificial intelligence and...
This growth has also spurred increased demand for machine learning skills, creating a massive opportunity for tech professionals to apply their knowledge in innovative new ways. But the skills needed to thrive in machine learning are, like the industry itself, ever evolving. ...