Looking forward, the team aims to scale these models for larger, more complex datasets and explore further optimizations in quantum state encoding and quantum machine learning architecture design.

Small-scale quantum computers can enhance machine learning performance, as shown in an experimental study using a photonic ...

An interdisciplinary team of researchers developed a machine learning tool to parse ... Neural Networks as an Interpretable Architecture for Image-like Quantum Matter Data," published June 23 ...

The deep-learning networks that have ... s first perceptron implemented on a quantum computer and then put it through its paces on some simple image processing tasks. In its simplest form, a ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning ... (such as fraud detection and image recognition) and predictive analytics ...

Quantum mechanics, which is the study of the behavior of sub-atomic particles, provides a way to enhance the use of machine ... the neural network architecture used in deep learning on classical ...

For 2023, she predicts that quantum algorithms have the potential to perform certain machine learning tasks faster and more accurately, especially for tasks such as image and speech recognition ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...