Driven by the rapid progress in quantum hardware, recent years have witnessed a furious
race for quantum technologies in both academia and industry. Universal quantum …

Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …

Quantum physics has changed the way we understand our environment, and one of its
branches, quantum mechanics, has demonstrated accurate and consistent theoretical …

The ZX-calculus is a graphical language for reasoning about quantum computation that has
recently seen an increased usage in a variety of areas such as quantum circuit optimisation …

Abstract Quantum Natural Language Processing (QNLP) deals with the design and
implementation of NLP models intended to be run on quantum hardware. In this paper, we …

In this paper, we propose a general scheme to analyze the gradient vanishing phenomenon,
also known as the barren plateau phenomenon, in training quantum neural networks with …

Generative modeling using samples drawn from the probability distribution constitutes a
powerful approach for unsupervised machine learning. Quantum mechanical systems can …

Powerful hardware services and software libraries are vital tools for quickly and affordably
designing, testing, and executing quantum algorithms. A robust large‐scale study of how the …

Deep Neural Network (DNN) models have been shown to have high empirical privacy
leakages. Clinical language models (CLMs) trained on clinical data have been used to …