Browsing Institutt for matematiske fag by Title
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Auslander–Reiten Triangles and Grothendieck Groups of Triangulated Categories
(Peer reviewed; Journal article, 2021)We prove that if the Auslander–Reiten triangles generate the relations for the Grothendieck group of a Hom-finite Krull–Schmidt triangulated category with a (co)generator, then the category has only finitely many isomorphism ... -
Authenticated Key Exchange and Signatures with Tight Security in the Standard Model
(Peer reviewed; Journal article, 2021)We construct the first authenticated key exchange protocols that achieve tight security in the standard model. Previous works either relied on techniques that seem to inherently require a random oracle, or achieved only ... -
Automatic Differentiation in Julia with Applications to Numerical Solution of PDEs
(Master thesis, 2019)Denne masteroppgaven gir en introduksjon til automatisk derivasjon (AD) og hvordan det kan benyttes til å beregne den deriverte til hvilken som helst funksjon, med samme presisjon som et analytisk uttrykk, men uten å innføre ... -
Automatic Parametrisation and Block pseudo Likelihood Estimation for binary Markov random Fields
(Master thesis, 2008)Discrete Markov random fields play an important role in spatial statistics, and are applied in many different areas. Models which consider only pairwise interaction between sites such as the Ising model often perform well ... -
Automorphisms of C<sup>k</sup>with an invariant non-recurrent attracting Fatou component biholomorphic to C×(C∗)<sup>k-1</sup>
(Journal article; Peer reviewed, 2021) -
Autoregressive Normalising Flows for Density Estimation and Variational Inference: A proper introduction and a novel flow
(Master thesis, 2020)I denne oppgaven presenterer vi en klasse med modeller kalt "normalising flows". Dette er en klasse med modeller som drar nytte av fleksibiliteten og de beregningsmessige fordelene som tilbys av det moderne dyp lærings-paradigmet, ... -
B-series for SDEs with application to exponential integrators for non-autonomous semi-linear problems
(Journal article; Peer reviewed, 2024)In this paper a set of previous general results for the development of B–series for a broad class of stochastic differential equations has been col- lected. The applicability of these results is demonstrated by the derivation ... -
B-stability of numerical integrators on Riemannian manifolds
(Peer reviewed; Journal article, 2024)We propose a generalization of nonlinear stability of numerical one-step integrators to Riemannian manifolds in the spirit of Butcher's notion of B-stability. Taking inspiration from Simpson-Porco and Bullo, we introduce ... -
B-stability of numerical integrators on Riemannian manifolds
(Peer reviewed; Journal article, 2024)We propose a generalization of nonlinear stability of numerical one-step integrators to Riemannian manifolds in the spirit of Butcher's notion of B-stability. Taking inspiration from Simpson-Porco and Bullo, we introduce ... -
Backtesting counterparty credit exposure based on the Heath, Jarrow and Morton framework for simulation of interest rates
(Master thesis, 2018)In this thesis a framework for backtesting counterparty credit exposure is developed and implemented. Using the Heath, Jarrow and Morton model for simulation of interest rates, separate models are implemented for risk-neutral ... -
Backward-Leak Uni-Directional Updatable Encryption from (Homomorphic) Public Key Encryption
(Peer reviewed; Journal article, 2023)The understanding of directionality for updatable encryption (UE) schemes is important, but not yet completed in the literature. We show that security in the backward-leak uni-directional key updates setting is equivalent ... -
Bandwidth Selection in Kernel Density Estimation
(Master thesis, 2010)In kernel density estimation, the most crucial step is to select a proper bandwidth (smoothing parameter). There are two conceptually different approaches to this problem: a subjective and an objective approach. In this ... -
Bandwith selection based on a special choice of the kernel
(Master thesis, 2007)We investigate methods of bandwidth selection in kernel density estimation for a wide range of kernels, both conventional and non-conventional. -
Bankruptcy prediction for Norwegian enterprises using interpretable machine learning models with a novel timeseries problem formulation
(Master thesis, 2020)Prediksjon av konkurs hos selskaper er et emne som er relevant både hos investorer, kreditorer, banker og regulatorer. I denne oppgaven bruker vi et datasett bestående av årsrapporter fra mer enn 175 000 norske små- og ... -
Barnard's CSM Test
(Bachelor thesis, 2020)I 1945 publiserte George Barnard en artikkel som beskrev en ny eksakt test for to gange to krysstabeller. Han hevdet at den gav høyere teststyrke enn Fishers eksakte test, noe som førte til en disputt over en serie artikler. ... -
Batch seismic inversion using the iterative ensemble Kalman smoother
(Peer reviewed; Journal article, 2021)An ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main focus of this work is the challenge associated with ensemble-based inversion ... -
Bayesian 4D inversion: integrating time-shift information
(Master thesis, 2006)A new inversion method for time-lapse seismic data is developed. The method is based on the 3-dimensional spatially coupled AVO inversion in the Fourier domain, describedin Buland et al. (2003b). Further, a technique for ... -
Bayesian analysis of latent Gaussian models
(Doktoravhandlinger ved NTNU, 1503-8181; 2014:249, Doctoral thesis, 2014) -
Bayesian Calibration and Inference for Multiple Machines
(Master thesis, 2019)I denne oppgaven, blir simuleringsmodeller, også kalt simulatorer, brukt til utføre prediksjon på maskiner. En av utfordringene med å gjøre prediksjon med simuleringsmodeller, er at de ikke fullt beskriver den sanne prosessen ... -
Bayesian Calibration for Modelling the Cardiovascular System Using the Two Element Windkessel Model
(Master thesis, 2022)Denne oppgaven utforsker egenskapene til Windkessel-modellene basert på syntetiske simuleringsstudier, og er en del av det tverrfaglige prosjektet "My Medical Digital Twin" ved NTNU. Windkessel-modellene estimerer de globale ...