Quantum computing (QC) stands apart from traditional computing systems by employing
revolutionary techniques for processing information. It leverages the power of quantum bits …

Quantum computing, based on quantum theory, holds great promise as an advanced
computational paradigm for achieving fast computations. Quantum algorithms are expected …

In this work, we aim to solve a practical use-case of unsupervised clustering that has
applications in predictive maintenance in the energy operations sector using quantum …

Recently, more researchers are interested in the domain of quantum machine learning as it
can manipulate and classify large numbers of vectors in high dimensional space in …

In this dissertation, our goal is to provide less complex solutions using pure quantum
algorithms as well as quantum machine learning algorithms, to deal with problems in the …

Finding the failure scenarios of a system is a very complex problem in the field of
Probabilistic Safety Assessment (PSA). In order to solve this problem we will use the Hidden …

Quantum networks have the potential to bring many novel applications to communication
networks and distributed computing, leading to more secure communication, accelerated …

The goal of Machine Learning is to teach the machine how to perform a specific task, without
providing explicit instructions. It is divided in three main families: supervised learning …

Cette thèse se situe à la frontière entre l'informatique quantique et l'apprentissage artificiel et
a pour objectif le traitement des données dans de très grandes dimensions. L'apprentissage …