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Showing result 1 - 5 of 22 essays matching the above criteria.

  1. 1. Model Based Testing for Programmable Data Planes

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Gustav Rixon; [2023]
    Keywords : Model Based Testing; Programmable Data Planes; P4; Software- Defined Networking;

    Abstract : The advent of Software Defined Networking (SDN) and programmable data planes has revolutionized the networking domain, enabling the programming of networking functions down to the silicon level responsible for data packet switching. Unfortunately, while this programmability offers greater flexibility and control, it also increases the likelihood of introducing software bugs. READ MORE

  3. 2. Exploring Normalizing Flow Modifications for Improved Model Expressivity

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Marcel Juschak; [2023]
    Keywords : Normalizing Flows; Motion Synthesis; Invertible Neural Networks; Glow; MoGlow; Maximum Likelihood Estimation; Generative models; normaliserande flöden; rörelsesyntes; inverterbara neurala nätverk; Glow; MoGlow; maximum likelihood-skattning generativa modeller;

    Abstract : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. READ MORE

  4. 3. Analyzing the Negative Log-Likelihood Loss in Generative Modeling

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Aleix Espuña I Fontcuberta; [2022]
    Keywords : Generative modeling; Normalizing flows; Generative Adversarial Networks; MaximumLikelihood Estimation; Real Non-Volume Preserving flow; Fréchet Inception Distance; Misspecification; Generativa metoder; Normalizing flows; Generative adversarial networks; Maximum likelihood-metoden; Real non-volume preserving flow; Fréchet inception distance; felspecificerade modeller;

    Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE

  5. 4. Quantification of cerebral blood flow with 15O-water PET : A comparison study between PET/CT and PET/MR and two different blood sampling instruments

    University essay from Umeå universitet/Institutionen för fysik; Umeå universitet/Diagnostisk radiologi

    Author : Amanda Eriksson; [2021]
    Keywords : Cerebral Blood Flow; CBF; oxygen-15-labelled water; PET CT; PET MR; Quantification of CBF; Image Derived Input Function; IDIF; Blood Sampled Input Function; BSIF; Arterial Input Function; AIF; Tracer Kinetic Modelling; Single Tissue Compartmental Model; 1TCM;

    Abstract : Cerebral blood flow quantification is a vital diagnostic tool for disease monitoring and used for diagnosing a variation of pathological conditions. The human brain requires roughly about 20 % of the total cardiac output to sustain normal functioning, hence the perfusion of blood is an important factor to deliver oxygenated blood. READ MORE

  6. 5. Modeling asymmetry in volatility response - non-Gaussian innovations approach

    University essay from Lunds universitet/Statistiska institutionen

    Author : Ludvig Göransson; [2020]
    Keywords : ARCH; GARCH; APARCH; Asymmetric GARCH; non-Gaussian innovations; Laplace distribution; Leverage effect; Stylized facts; Volatility process.; Mathematics and Statistics;

    Abstract : This thesis is an explorative note on the non-Gaussian innovations of the volatility process. More specifically, the thesis investigates if the decomposition of the Standard Classical Laplace (SCL) distribution to a difference of two exponential is a valid alternative to modelling the asymmetric volatility processes, taking volatility clustering, the leverage effect and asymmetric response in volatility into account. READ MORE