Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

Quantum Machine Learning is an interdisciplinary field that harnesses the computational power of quantum systems to develop algorithms that can process and analyze data more efficiently than classical ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

A team of international physicists has brought Bayes’ centuries-old probability rule into the quantum world. By applying the ...

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...

Finding high-performing candidates in the vast search space of bosonic qubit encodings represents a complex optimization task, which the researchers address with reinforcement learning, an advanced ...

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 ...