Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Innatera’s Pulsar blends analog and digital SNN accelerators to deliver always-on neural-network operation for low-power applications. 1. Innatera’s Pulsar system-on-chip incorporates analog and ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

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

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

The researchers suggest that this improvement in diagnostic performance for OFC biomarker discovery can be used to develop a diagnostic alternative for food allergy that is scalable and more efficient ...

The Nobel Prize in physics has been awarded to John J. Hopfield of Princeton University and Geoffrey E. Hinton of the University of Toronto for discoveries and inventions that formed the building ...

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

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...