A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

In machine learning, privacy risks often emerge from inference-based attacks. Model inversion techniques can reconstruct sensitive training data from model outputs. Membership inference attacks allow ...

AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...

A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Researchers at the University of Maryland and Tilburg University in the Netherlands have produced an AI-driven innovation to ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

One example involved a system built by a summer intern for his own project work. The tool geolocates devices within a drawing set and links them to a digital twin of the facility. Instead of searching ...

For years, Iceland, Switzerland, and Norway have ranked near the top of the United Nations' annual index of countries based on indicators of well-being and quality of life. Countries with more poverty ...

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

A recent study suggests that a freely available AI tool could help predict dangerous complications after stem cell transplants.