Department of Mathematics
Nye registreringer
-
Evaluating the suitability of close-kin mark-recapture as a demographic modelling tool for a critically endangered elasmobranch population
(Journal article; Peer reviewed, 2022)Estimating the demographic parameters of contemporary populations is essential to the success of elasmobranch conservation programmes, and to understanding their recent evolutionary history. For benthic elasmobranchs such ... -
A gentle tutorial on accelerated parameter and confidence interval estimation for hidden Markov models using Template Model Builder
(Journal article; Peer reviewed, 2022)A very common way to estimate the parameters of a hidden Markov model (HMM) is the relatively straightforward computation of maximum likelihood (ML) estimates. For this task, most users rely on user-friendly implementation ... -
Modeling the Process of Speciation Using a Multiscale Framework Including A Posteriori Error Estimates
(Journal article; Peer reviewed, 2022)This paper concerns the modeling and numerical simulation of the process of speciation. In particular, given conditions for which one or more speciation events within an ecosystem occur, our aim is to develop the necessary ... -
A horizontal Chern–Gauss–Bonnet formula on totally geodesic foliations
(Journal article; Peer reviewed, 2022)Under suitable conditions, we show that the Euler characteristic of a foliated Riemannian manifold can be computed only from curvature invariants which are transverse to the leaves. Our proof uses the hypoelliptic sub-Laplacian ... -
Threshold estimation based on local minima for nucleus and cytoplasm segmentation
(Journal article; Peer reviewed, 2022)Background Image segmentation is the process of partitioning an image into separate objects or regions. It is an essential step in image processing to segment the regions of interest for further processing. We propose a ... -
Wave response to an arbitrary motion of a load on an ice plate
(Master thesis, 2022-06-22) -
Hybrid Modeling of the N-Body Problem with Applications to Astrophysics
(Master thesis, 2022-06-01)Over the last years, the field of hybrid modeling, the concept of combining data-driven machine learning models and numerical solution methods to simulate a physical system, has seen an immense increase in research. This ... -
Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer
(Journal article; Peer reviewed, 2022-05-11)Uterine cervical cancer (CC) is the most common gynecologic malignancy worldwide. Whole-volume radiomic profiling from pelvic MRI may yield prognostic markers for tailoring treatment in CC. However, radiomic profiling ... -
A posteriori error estimation and modeling of unsaturated flow in fractured porous media
(Doctoral thesis, 2022-06-17)This doctoral thesis focuses on three topics: (1) modeling of unsaturated flow in fractured porous media, (2) a posteriori error estimation for mixed-dimensional elliptic equations, and (3) contributions to open-source ... -
A Finite-Volume-Based Module for Unsaturated Poroelasticity
(Chapter, 2021)In this chapter, we present fv-unsat, a multipoint finite-volume–based solver for unsaturated flow in deformable and nondeformable porous media. The latter is described using the mixed form of Richards’ equation, whereas ... -
Socioeconomic and geographic differences in ablation of atrial fibrillation in Norway - a national cohort study
(Journal article; Peer reviewed, 2022)Background The aim of this study was to analyse whether there are patient related or geographic differences in the use of catheter ablation among atrial fibrillation patients in Norway. Methods National population-based ... -
Interdisciplinary and Transferable Concepts in Bioinformatics Education: Observations and Approaches From a UK MSc Course
(Journal article; Peer reviewed, 2022-02-24)Bioinformatics is a highly interdisciplinary subject, with substantial and growing influence in health, environmental science and society, and is utilised by scientists from many diverse academic backgrounds. Education in ... -
Modelling clusters of corporate defaults: Regime-switching models significantly reduce the contagion source
(Journal article; Peer reviewed, 2022)In this paper, we report robust evidence that the process of corporate defaults is time-dependent and can be modelled by extending an autoregressive count time series model class via the introduction of regime-switching. ... -
Rotational effects on exchange flows across a submerged sill
(Journal article; Peer reviewed, 2021)This paper presents new laboratory-scale numerical simulations of density-driven exchange flows generated across an idealised, submerged sill obstruction under both non-rotating and rotating frames of reference using the ... -
Hidden semi-Markov-switching quantile regression for time series
(Journal article; Peer reviewed, 2021)A hidden semi-Markov-switching quantile regression model is introduced as an extension of the hidden Markov-switching one. The proposed model allows for arbitrary sojourn-time distributions in the states of the Markov-switching ... -
Dispersive Estimates for Full Dispersion KP Equations
(Journal article; Peer reviewed, 2021)We prove several dispersive estimates for the linear part of the Full Dispersion Kadomtsev–Petviashvili introduced by David Lannes to overcome some shortcomings of the classical Kadomtsev–Petviashvili equations. The proof ... -
A mathematical justification of the momentum density function associated to the KdV equation
(Journal article; Peer reviewed, 2021)Consideration is given to the KdV equation as an approximate model for long waves of small amplitude at the free surface of an inviscid fluid. It is shown that there is an approximate momentum density associated to the KdV ... -
Optimal strategies in the Fighting Fantasy gaming system: influencing stochastic dynamics by gambling with limited resource
(Journal article; Peer reviewed, 2022)In many games and other processes, participants can choose to intervene in some way that does not follow the usual progress of the game (for example, cheating at cards, or spying on rivals) which may provide benefits, but ... -
Epistemic Uncertainty Quantification in Deep Learning by the Delta Method
(Doctoral thesis, 2022-05-16)This thesis explores the Delta method and its application to deep learning image classification. The Delta method is a classical procedure for quantifying uncertainty in statistical models, but its direct application to ...
RSS 2.0