Martin Jullum
Martin Jullum
Norwegian Computing Center
Geverifieerd e-mailadres voor nr.no
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Explaining individual predictions when features are dependent: More accurate approximations to Shapley values
K Aas, M Jullum, A Løland
arXiv preprint arXiv:1903.10464, 2019
502019
A Gaussian-based framework for local Bayesian inversion of geophysical data to rock properties
M Jullum, O Kolbjørnsen
Geophysics 81 (3), R75-R87, 2016
312016
Parametric or nonparametric: The FIC approach
M Jullum, NL Hjort
Statistica Sinica, 951-981, 2017
252017
Bayesian AVO inversion to rock properties using a local neighborhood in a spatial prior model
O Kolbj⊘ rnsen, A Buland, R Hauge, P R⊘ e, M Jullum, RW Metcalfe, ...
The Leading Edge 35 (5), 431-436, 2016
152016
What price semiparametric Cox regression?
M Jullum, NL Hjort
Lifetime data analysis 25 (3), 406-438, 2019
142019
Detecting money laundering transactions with machine learning
M Jullum, A Løland, RB Huseby, G Ånonsen, J Lorentzen
Journal of Money Laundering Control, 2020
62020
shapr: An R-package for explaining machine learning models with dependence-aware Shapley values
N Sellereite, M Jullum
Journal of Open Source Software 5 (46), 2027, 2020
42020
Parametric or nonparametric: the FIC approach for stationary time series
GH Hermansen, NL Hjort, M Jullum
Proceedings of the 60th World Statistics Congress of the International …, 2015
22015
Pairwise local Fisher and naive Bayes: Improving two standard discriminants
H Otneim, M Jullum, D Tjøstheim
Journal of Econometrics 216 (1), 284-304, 2020
12020
Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling
M Jullum, T Thorarinsdottir, FE Bachl
Journal of the Royal Statistical Society: Series C (Applied Statistics) 69 …, 2020
12020
New focused approaches to topics within model selection and approximate Bayesian inversion
M Jullum
PhD Thesis, University of Oslo, 2016
12016
An approximate Bayesian inversion framework based on local-Gaussian likelihoods
M Jullum, O Kolbjørnsen
Petroleum Geostatistics 2015, cp-456-00050, 2015
12015
Focused Information criteria for selecting among parametric and nonparametric models
M Jullum
Master Thesis, University of Oslo, Norway, 2012
12012
Explaining predictive models using Shapley values and non-parametric vine copulas
K Aas, T Nagler, M Jullum, A Løland
arXiv preprint arXiv:2102.06416, 2021
2021
Explaining predictive models with mixed features using Shapley values and conditional inference trees
A Redelmeier, M Jullum, K Aas
International Cross-Domain Conference for Machine Learning and Knowledge …, 2020
2020
Investigating mesh‐based approximation methods for the normalization constant in the log Gaussian Cox process likelihood
M Jullum
Stat 9 (1), e285, 2020
2020
Estimating seal pup production in the Greenland
M Jullum
2018
Statistical modeling of repertoire overlap in entire sampling spaces
L Holden, M Jullum, GK Sandve, L Holden, M Jullum, GK Sandve
2017
Vindprognoser og strømpriser
M Jullum
NR-note, 21, 2011
2011
ESTIMATING SEAL PUP PRODUCTION IN THE GREENLAND SEA USING BAYESIAN HIERARCHICAL MODELING (ONLINE SUPPLEMENTARY MATERIAL)
M JULLUM, T THORARINSDOTTIR, FE BACHL
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Artikelen 1–20