A supplemental investigation of non-linearity in quantum generative models with respect to simulatability and optimization

no code implementations • 1 Feb 2023 • Kaitlin Gili, Rohan S. Kumar, Mykolas Sveistrys, C. J. Ballance

As a follow-up to this work, we investigate two questions of relevance to the quantum algorithms and machine learning communities: Does introducing this form of non-linearity make the learning model classically simulatable due to the deferred measurement principle?

Introducing Non-Linear Activations into Quantum Generative Models

no code implementations • 28 May 2022 • Kaitlin Gili, Mykolas Sveistrys, Chris Ballance

In this paper, we explore the effect of these dynamics in quantum generative modeling by introducing a model that adds non-linear activations via a neural network structure onto the standard Born Machine framework - the Quantum Neuron Born Machine (QNBM).