During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …

The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …

Quantum computing promises to enhance machine learning and artificial intelligence.
However, recent theoretical works show that, similar to traditional classifiers based on deep …

Quantum neural networks (QNNs) have become an important tool for understanding the
physical world, but their advantages and limitations are not fully understood. Some QNNs …

Deep learning and quantum computing have achieved dramatic progresses in recent years.
The interplay between these two fast-growing fields gives rise to a new research frontier of …

Variational quantum algorithms (VQAs) are promising methods to demonstrate quantum
advantage on near-term devices as the required resources are divided between a quantum …

Although near-term quantum computing devices are still limited by the quantity and quality of
qubits in the so-called NISQ era, quantum computational advantage has been …

Abstract Machine learning has achieved dramatic success over the past decade, with
applications ranging from face recognition to natural language processing. Meanwhile, rapid …

The resurgence of self-supervised learning, whereby a deep learning model generates its
own supervisory signal from the data, promises a scalable way to tackle the dramatically …

Quantum neural networks (QNNs) have become an important tool for understanding the
physical world, but their advantages and limitations are not fully understood. Some QNNs …