Recent advances in classical machine learning have shown that creating models with
inductive biases encoding the symmetries of a problem can greatly improve performance …

Data compression can be achieved by reducing the dimensionality of high-dimensional but
approximately low-rank datasets, which may in fact be described by the variation of a much …

As a ubiquitous aspect of modern information technology, data compression has a wide
range of applications. Therefore, a quantum autoencoder which can compress quantum …

A universal quantum processor is a device that takes as input a (quantum) program,
containing an encoding of an arbitrary unitary gate, and a (quantum) data register, on which …

The ability to extract relevant information is critical to learning. An ingenious approach as
such is the information bottleneck, an optimisation problem whose solution corresponds to a …

Quantum data compression is of great significance to both quantum computation and
quantum communication due to the limited resources for quantum storage. Here in this …

Advances in development of quantum computing processors brought ample opportunities to
test the performance of various quantum algorithms with practical implementations. In this …

Error correcting codes with a universal set of transversal gates are a desideratum for
quantum computing. Such codes, however, are ruled out by the Eastin-Knill theorem …

We establish the ultimate limits to the compression of sequences of identically prepared
qubits. The limits are determined by Holevo's information quantity and are attained through …

Edge computing aims to address the challenges associated with communicating and
transferring large amounts of data generated remotely to a data center in a timely and …