17-659 — Generative AI for Quantum Computing and Machine Learning Software Implementations — Summer Semester 2023

June 13 / Week 5

Quantum Generative Models

Quantum generative models are like a magician’s hat 🎩. You never know what you’re going to get! They use quantum mechanics to generate new data and are used in various applications such as the generation of probability distributions, drugs, and option pricing for financial applications. In quantum generative models, the underlying probability distribution describing correlations in data is generated by measuring a set of observables under a many-body entangled state. The goal of generative machine learning is to model the probability distribution underlying a given data set. This probability distribution helps to characterize the generation process of the data samples.

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