Study and Implementation of Quantum Bayesian Networks

This project deals with the implementation of Bayesian networks, a type of artificial intelligence based on graph theory and conditional probability, in the quantum computing paradigm. Examples related to the world of sports will be used as input in order to test the developed model. Besides, a comparison between implementations in classical and quantum paradigms will be carried out, so their differences in performance and attributes can be appreciated. The work will conclude with a debate about quantum computing and its future as a basis for executing AI models.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.17979/spudc.9788497498913.16
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
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article

Study and Implementation of Quantum Bayesian Networks

Alejandro Mayorga Redondo, Vicente Moret Bonillo
Bayesian Modeling and Causal Inference
article

Study and Implementation of Quantum Bayesian Networks

Alejandro Mayorga Redondo, Vicente Moret Bonillo
article en

Abstract

This project deals with the implementation of Bayesian networks, a type of artificial intelligence based on graph theory and conditional probability, in the quantum computing paradigm. Examples related to the world of sports will be used as input in order to test the developed model. Besides, a comparison between implementations in classical and quantum paradigms will be carried out, so their differences in performance and attributes can be appreciated. The work will conclude with a debate about quantum computing and its future as a basis for executing AI models.

Openalex Percentile: Top 75%
Bayesian Modeling and Causal Inference
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Study and Implementation of Quantum Bayesian Networks — Alejandro Mayorga Redondo, Vicente Moret Bonillo · (2024) | TGRS Research Map | TGRS