Searched for: subject%3A%22Information%255C%2BTheory%22
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Alers, Tim (author)
The visibility graph has gained traction as a method for time series analysis. Through this method, it is possible to detect or quantify non-linear behavior in a myriad of fields and applications. This thesis explores the variations of visibility graphs, describes how they are used in literature and investigates what lies at the foundation of...
master thesis 2023
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Szkudlarek, Sacha (author)
This thesis presents a novel formulation to study the qubit-mapping problem (QMP). The presented for- mulation redefines the problem in terms of density matrices which represent the quantum algorithm and the underlying architecture—allowing the implementation of techniques from quantum information theory to es- tablish a bounded metric space for...
master thesis 2023
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Hautelman, Alex (author)
Bayesian optimisation is a rapidly growing area of research that aims to identify the optimum of the black-box function, as it strategically directs the optimisation process towards promising regions. This paper provides an overview of the theoretical background used by the Entropy Search algorithms under study, mainly Predictive Entropy Search,...
bachelor thesis 2023
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Vasilev, Kiril (author)
The data used in machine learning algorithms strongly influences the algorithms' capabilities. Feature selection techniques can choose a set of columns that meet a certain learning goal. There is a wide variety of feature selection methods, however, the ones we cover in this comparative analysis are part of the information-theoretical-based...
bachelor thesis 2023
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de Rijke, Demi (author)
This study focuses on optimizing the use of high-performance computing on public cloud infrastructure, along with information theory, for assessing water systems. These assessments are computationally intensive and can benefit from parallel computing and the evaluation of the collected data with information theory. A case study of a water system...
master thesis 2023
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Sarkar, A. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)
In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum information theory on density matrices. Quantum process...
conference paper 2023
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van Poelgeest, Sam (author)
In the field of quantum information theory, it is well-known that the purely quantum phenomenon called quantum entanglement can boost the capacity of a quantum channel, which is called the superadditivity of the capacity. Shor showed in his breakthrough paper on the equivalence of additivity conjectures that this superadditivity is equivalent to...
master thesis 2022
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Sarkar, A. (author)
Efforts to realize a sufficiently large controllable quantum processor are actively being pursued globally. These quantum devices are programmed by specifying the manipulation of quantum information via quantum algorithms. This doctoral research provides an application perspective to the design requirements of a quantum accelerator architecture....
doctoral thesis 2022
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SAMIOTIS, MARIOS (author)
In this work, we first analyse a theoretical technique based on entropic inequalities, which in principle can be used to compare classical and quantum algorithms running on noisy quantum devices. The technique has been used in the past for depolarizing noise, and has shown that for NISQ variational quantum algorithms (VQAs) to give an advantage...
master thesis 2022
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Goodenough, K.D. (author)
The research presented in this thesis focused on the problem of entanglement distribution. Simply put, the two main problems facing (practical) implementation of entanglement distribution over quantum networks are loss and noise. Quantum repeaters are meant to overcome the effects of loss, but in practice their implementation always comes at the...
doctoral thesis 2022
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Li, G. (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Accurate short-term traffic forecasting is the cornerstone for Intelligent Transportation Systems. In the past several decades, many models have been proposed to continuously improve the predictive accuracy. A key but unsolved question is whether there is a theoretical bound to the accuracy with which traffic can be predicted and whether that...
journal article 2022
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Dong, Thi Ngan (author), Mucke, Stefanie (author), Khosla, M. (author)
Growing evidence from recent studies implies that microRNAs or miRNAs could serve as biomarkers in various complex human diseases. Since wet-lab experiments for detecting miRNAs associated with a disease are expensive and time-consuming, machine learning techniques for miRNA-disease association prediction have attracted much attention in...
journal article 2022
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Sarkar, A. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)
Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target...
journal article 2021
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van Houte, Roy (author)
Quantum coin flipping is a cryptographic primitive in which two or more parties that do not trust each other want establish a fair coin flip. These parties are not physically near each other and use quantum communication channels to interact. A quality of protocols is measured by the best possible cheating strategy, which is the solution of a...
master thesis 2020
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Vos, Gerrit (author)
Tsirelson once claimed that the set of quantum correlations, defined by strategies of non-local two-player games, does not depend on which of two possible models is chosen: the tensor product model or the commuting operator model. He later came back from this claim, and the resulting conjecture is now known as Tsirelson’s problem. The problem...
master thesis 2019
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Elkouss Coronas, D. (author), Pérez-García, David (author)
Most communication channels are subjected to noise. One of the goals of information theory is to add redundancy in the transmission of information so that the information is transmitted reliably and the amount of information transmitted through the channel is as large as possible. The maximum rate at which reliable transmission is possible is...
journal article 2018
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van Erp, H.R.N. (author)
We present here a Bayesian framework of risk perception. This framework encompasses plausibility judgments, decision making, and question asking. Plausibility judgments are modeled by way of Bayesian probability theory, decision making is modeled by way of a Bayesian decision theory, and relevancy judgments are modeled by way of a Bayesian...
doctoral thesis 2017
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Ng, N.H.Y. (author)
Thermodynamics is one of the main pillars of theoretical physics, and it has a special appeal of having wide applicability to a large variety of different physical systems. However, many assumptions in thermodynamics apply only to systems which are bulk material, i.e. consisting a large number of microscopic classical particles. Due to the...
doctoral thesis 2017
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van Erp, H.R.N. (author), Linger, R.O. (author), van Gelder, P.H.A.J.M. (author)
In this paper, we will give the derivation of an inquiry calculus, or, equivalently, a Bayesian information theory. From simple ordering follow lattices, or, equivalently, algebras. Lattices admit a quantification, or, equivalently, algebras may be extended to calculi. The general rules of quantification are the sum and chain rules. Probability...
journal article 2017
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Bernhard, M. (author)
“Frequency analysis of wood textures” presents the application of Fourier analysis to translate images of wood textures to the frequency domain. With this encoding, a lot more details can be captured by the same amount of data points than with other descriptions in the spatial domain. A small set of overlapping waves with different frequencies,...
conference paper 2013
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