Blar i Institutt for matematiske fag på tittel
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Geostatistical Analysis of DHS Data: Accounting for Random Displacement of Survey Locations
(Doctoral theses at NTNU;2023:184, Doctoral thesis, 2023) -
Geostatistical Modeling under Positional Uncertainty
(Master thesis, 2023)I denne oppgaven undersøker vi posisjonell usikkerhet i geostatistisk modellering. Et sentralt eksempel på posisjonell usikkerhet er bruken av geografisk maskering (geomaskering) ment til å beskytte personvern. Geomaskering ... -
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
(Peer reviewed; Journal article, 2022)We present a Bayesian geostatistical model for mean annual runoff that incorporates simulations from a process-based hydrological model. The simulations are treated as a covariate and the regression coefficient is modeled ... -
Global Bifurcation of a Nonlocal Equation
(Master thesis, 2022)Vi studerer en dispersiv likning av typen fraksjonell Korteweg–de Vrie [38, 46] med en ikke-lokal ikkelineæritet som er en Coifman–Meyer operator [14], som når betraktet i stabile variabler antar formen -µϕ + Λ^s ϕ + ϕ Λ^r ... -
Global bifurcation of waves with multiple critical layers
(Journal article; Peer reviewed, 2020)Analytic global bifurcation theory is used to construct a large variety of families of steady periodic two-dimensional gravity water waves with real-analytic vorticity distributions, propagating in an incompressible fluid. ... -
Global Buckling Reliability Analysis of Slender Network Arch Bridges: An Application of Monte Carlo-Based Estimation by Optimized Fitting
(Chapter, 2017)Network arch bridges are extremely slender bridge structures with a very efficient 16 load-carrying structure. This configuration can carry loads that are several times greater 17 than traditional tied-arch bridges with ... -
Global dissipative solutions of the two-component Camassa-Holm system for initial data with nonvanishing asymptotics
(Journal article, 2014)We show the existence of a global weak dissipative solution of the Cauchy problem for the two-component Camassa–Holm (2CH) system on the line with nonvanishing and distinct spatial asymptotics. The influence from the second ... -
Global existence of dissipative solutions to the Camassa--Holm equation with transport noise
(Peer reviewed; Journal article, 2023)We consider a nonlinear stochastic partial differential equation (SPDE) that takes the form of the Camassa–Holm equation perturbed by a convective, position-dependent, noise term. We establish the first global-in-time ... -
Global Models for Time Series Forecasting With Applications to Zero-Shot Forecasting
(Master thesis, 2021)Globale tidsrekkemodeller er tilpasset til et sett med tidsrekker. Dette er i motsetning til lokale tidsrekkemodeller som er tilpasset individuelle tidsrekker. En global tilnærming kan motvirke overtilpasning siden vi ... -
Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA
(Journal article; Peer reviewed, 2024)Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, ... -
Global well-posedness of the viscous Camassa–Holm equation with gradient noise
(Peer reviewed; Journal article, 2022)We analyse a nonlinear stochastic partial differential equation that corresponds to a viscous shallow water equation (of the Camassa–Holm type) perturbed by a convective, position-dependent noise term. We establish the ... -
Globally proper efficiency of set optimization problems based on the certainly set less order relation
(Peer reviewed; Journal article, 2023)In this paper, we investigate the globally proper efficiency of set optimization problems. Firstly, we use the so-called certainly set less order relation to define a new kind of set order relation. Based on the new set ... -
Going relative with Maurice—a survey
(Journal article, 2018) -
Gorenstein weak global dimension is symmetric
(Peer reviewed; Journal article, 2021)We study the Gorenstein weak global dimension of associative rings and its relation to the Gorenstein global dimension. In particular, we prove the conjecture that the Gorenstein weak global dimension is a left-right ... -
GPU Computing with Python: Performance, Energy Efficiency and Usability
(Journal article; Peer reviewed, 2020)In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of ... -
Graded-material design based on phase-field and topology optimization
(Journal article; Peer reviewed, 2019)In the present work we introduce a novel graded-material design based on phase-field and topology optimization. The main novelty of this work comes from the introduction of an additional phase-field variable in the classical ... -
The gradient flow of infinity-harmonic potentials
(Peer reviewed; Journal article, 2021)We study the streamlines of ∞-harmonic functions in planar convex rings. We include convex polygons. The points where streamlines can meet are characterized: they lie on certain curves. The gradient has constant norm along ... -
Gradient-Based Optimization in Shape Analysis for Reparametrization of Parametric Curves and Surfaces
(Master thesis, 2021)I denne oppgaven studerer vi to gradientbaserte optimeringsalgoritmer i formanalyse, for reparametrisering av parametriske kurver og overflater. Den ene algoritmen er en tidligere kjent “gradient descent”-algoritme på ... -
Grafiske analysemetoder for ikke-geometriske design
(Master thesis, 2008)Den grafiske analyseringen av tonivåforsøk har lenge begrenset seg til Lenth's metode, normalplott og halvnormalplott. Disse plotta baserer seg på at de estimerte kontrastene enten representerer aktive effekter eller støy. ... -
Graph Gaussian Process Classifier with Anchor Graph and Label Propagation
(Master thesis, 2021)Gaussiske prosesser er en viktig metode for maskinlæring da den lar oss sette en prioritet p˚a formen til en funksjon, og den arver fine egenskaper fra normalfordelingen. Den har blitt brukt b˚ade som en regresjons- og ...