Browsing Institutt for matematiske fag by Title
Now showing items 553-572 of 2558
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d-abelian quotients of (d+2)-angulated categories
(Journal article; Peer reviewed, 2019)Let T be a triangulated category. If t is a cluster tilting object and I=add t is the ideal of morphisms factoring through an object of add t, then the quotient category T/I is abelian. This is an important result of cluster ... -
Data Analysis of Magnetotelluric Survey Data
(Master thesis, 2014)We study data from marine magnetotelluric (MT) surveys. In MT surveys the objective is to study the distribution of resistivity in the Earth's subsurface, and the quantity of interest is the impedance Z(ω). The impedance ... -
Data assimilation for a geological process model using the ensemble Kalman filter
(Journal article, 2017)We consider the problem of conditioning a geological process‐based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we ... -
Data Assimilation in Spatio-Temporal Models with Non-Gaussian Initial States—The Selection Ensemble Kalman Model
(Peer reviewed; Journal article, 2020)Assimilation of spatio-temporal data poses a challenge when allowing non-Gaussian features in the prior distribution. It becomes even more complex with nonlinear forward and likelihood models. The ensemble Kalman model and ... -
Data Integration for Large-Scale Models of Species Distributions
(Peer reviewed; Journal article, 2019)With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species’ potential and realized distributions ... -
Data Integration for Species Distribution Models
(Master thesis, 2020)I denne oppgaven blir fordelingen av ferskvannsfisk i norske innsjøer estimert ved å bruke data fra to standardiserte datasett og ett opportunistisk datasett sammen med miljøbaserte kovariater til å lage en kombinert modell. ... -
Data-driven and geometric numerical methods for mechanical systems
(Doctoral theses at NTNU;2024:240, Doctoral thesis, 2024) -
Data-driven Avalanche Forecasting - Using automatic weather stations to build a data-driven decision support system for avalanche forecasting
(Master thesis, 2016)In this paper, a decision support system for avalanche forecasting based on data from automatic weather stations is developed and tested. 17 years of avalanche and weather observations from Senja in Northern Norway are ... -
Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective
(Chapter, 2021)Routine cervical cancer screening at regular periodic intervals leads to either over-screening or too infrequent screening of patients. For this purpose, personalized screening intervals are desirable that account for ... -
Daubechies' time-frequency localization operator on Cantor type sets II
(Peer reviewed; Journal article, 2022)We study a version of the fractal uncertainty principle in the joint time-frequency representation. Namely, we consider Daubechies' localization operator projecting onto spherically symmetric n-iterate Cantor sets with an ... -
Decay and symmetry of solitary waves
(Peer reviewed; Journal article, 2022) -
Decay rates for approximation numbers of composition operators
(Journal article; Peer reviewed, 2015)A general method for estimating the approximation numbers of composition operators on the Hardy space H 2, using finite-dimensional model subspaces, is studied and applied in the case when the symbol of the operator maps ... -
Decoding of neural data using cohomological feature extraction
(Journal article; Peer reviewed, 2019)We introduce a novel data-driven approach to discover and decode features in the neural code coming from large population neural recordings with minimal assumptions, using cohomological feature extraction. We apply our ... -
Decomposing demographic contributions to the effective population size with moose as a case study
(Journal article; Peer reviewed, 2020)Levels of random genetic drift are influenced by demographic factors, such as mating system, sex ratio and age structure. The effective population size (Ne) is a useful measure for quantifying genetic drift. Evaluating ... -
Decomposition of Modules over finite-dimensional Algebras
(Master thesis, 2018)We investigate algorithms for decomposing a module $M$ over a finite-dimensional path algebra $\Lambda$. The algorithms first have to construct the endomorphism ring \[ \End(M) = \Hom(M, M). \] \noindent Consequently, ... -
Decompositions of nonlinear input–output systems to zero the output
(Journal article; Peer reviewed, 2024)Consider an input–output system where the output is the tracking error given some desired reference signal. It is natural to consider under what conditions the problem has an exact solution, that is, the tracking error is ... -
Decorated Marked Surfaces III: The Derived Category of a Decorated Marked Surface
(Journal article; Peer reviewed, 2021) -
Dedekind zeta functions
(Bachelor thesis, 2021)Vi gir en introduksjon til algebraisk tallteori med mål om å definere Dedekind-zetafunksjoner, samt bevise klassetallsformelen. Avslutningsvis bruker vi klassetallsformelen til å bevise Dirichlets teorem om primtall i ... -
Deep Learning Algorithms for Solving PDEs - Presentation and Implementation of Deep Learning Algorithms for Solving Semi-Linear Parabolic PDEs with an Extension to the Fractional Laplace Operator
(Master thesis, 2020)I juni 2017 presenterer Weinan E, Jiequn Han og Arnulf Jentzen en banebrytende algoritme, Deep Backward Stochastic Differential Equation (Deep BSDE), for å løse partielle differensiallikninger (PDEer) ved bruk av dyp læring. ... -
Deep learning as optimal control problems: models and numerical methods
(Journal article; Peer reviewed, 2019)We consider recent work of [11] and [6], where deep learning neuralnetworks have been interpreted as discretisations of an optimal control problemsubject to an ordinary differential equation constraint. We review the first ...