A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ...

Overview Curated list highlights seven impactful books covering fundamentals, tools, machine learning, visualization, and industry.Guides beginners and professi ...

Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras.Growing demand for AI profes ...

Despite significant mathematical refinements, econometrics has shown the weaknesses of its logical underpinnings, primarily during economic turning points—financial crises, pandemics, and geopolitical ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

The integration of advanced technologies into the energy sector has led to the emergence of smart grids, which promise enhanced efficiency, reliability, and sustainability in electricity distribution.

Quadratic regression is a classical machine learning technique to predict a single numeric value. Quadratic regression is an extension of basic linear regression. Quadratic regression can deal with ...

In the United States: The Equal Credit Opportunity Act (ECOA) and the Fair Credit Reporting Act (FCRA) require lenders to ...

Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldstein & Fox PLLC discuss challenges in meeting patent law's disclosure requirements for inventions involving artificial intelligence, ...