Ever wondered how quantum computers work, and how they do machine learning? With quantum computing technologies nearing the ear of commercialization and quantum advantage, machine learning has been proposed as one of the most promising applications. One of the areas in which quantum computing is showing great potential is in generative models in unsupervised and semi-supervised learning.
In this training you will develop a basic understanding of quantum computing and how it can be used in machine learning models, with special emphasis on generative models. We will focus on a particular architecture, the quantum circuit Born machine (QCBM), and use it to generate a simple dataset of bars and stripes.
No previous knowledge of quantum computing and generative model is needed for this workshop.
Training Overview and Authors Bio
Introduction to Generative Modeling Using Quantum Machine Learning
Quantum AI Research Scientist | Author of Grokking Machine Learning | Zapata Computing
Quantum Applications Intern | Zapata Computing
Alejandro Perdomo, PhD
Senior Quantum Scientist | Zapata Computing