Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Opinion: A patent case involving inventor Guillaume Desjardins has evolved into a cornerstone of modern patent eligibility ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of ...

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...