The integration of deep learning techniques and physics-driven designs is reforming the way we address inverse problems, in which accurate physical properties are extracted from complex observations.

Evolutionary computation, for example, particle swarm optimization, has impressive achievements in solving complex problems in science and industry; however, an important open problem in evolutionary ...

Sam Mugel, Ph.D., is the CTO of Multiverse Computing, a global leader in developing value-driven quantum solutions for businesses. Quantum mechanics, which is the study of the behavior of sub-atomic ...

However, by the late 1970s, there was disappointment that the two main approaches to computing in medicine — rule-based systems and matching, or pattern recognition, systems — had not been as ...

Artificial intelligence is transforming how we live and work, from personalized recommendations to health care innovation.

Classical machine learning (ML) is a powerful subset of artificial intelligence. Machine learning has advanced from simple pattern recognition in the 1960s to today's advanced use of massive datasets ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...