Large AI models can speed catalyst discovery by predicting performance before synthesis

Artificial intelligence (AI) is transforming the way scientists discover and design new materials. In a specially invited review published in Angewandte Chemie International Edition, Tohoku University ...
IEEE

Physically-Aware Qubit Reuse for Optimized Quantum Circuit Compilation Using Machine Learning

Recently developed quantum computers support mid-circuit measurements, allowing qubit measurement, resetting, and reuse during the execution of quantum circuits. This capability opens new ...
IEEE

Deep Carbonate Reservoir Hydrocarbon Detection Using Multiseismic Features Constrained Unsupervised Machine Learning

Abstract: Reservoir hydrocarbon detection is of great interest for reservoir characterization and quality assessment. However, deep carbonate reservoirs exhibit weak seismic response features, making ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...