The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

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

DUBLIN--(BUSINESS WIRE)--The "Semiconductor Cybersecurity Market - A Global and Regional Analysis: Focus on Application, Deployment Type, Solution, Security Type, and Region - Analysis and Forecast, ...