Webinar: Application of variational quantum algorithms for learning the structure of Bayesian networks.
Speaker: Vicente P. Soloviev, Quantum Machine Learning and IA researcher, Polytechnic University of Madrid (UPM).
Date and time: Tuesday, March 15, 2022, at 18:15h.
In this talk, the results obtained in the recent work carried out will be shown. A brief introduction to Bayesian networks (applications and concept) will be made in order to introduce the problem of learning the structure of Bayesian networks from data. Subsequently, the application of the variational Quantum Approximate Optimization Algorithm (QAOA) will be shown, and the results obtained, considering and not considering different types of quantum noise, on real datasets.
Link to work: https://arxiv.org/abs/2203.02400