Martin Jullum

Improving the weighting strategy in KernelSHAP 2025. Poster

Introduction to Local Model-Agnostic methods in XAI 2025. Faglig foredrag

Hva skjer når avfall møter algoritmer? , 2025. Programdeltagelse

AI/ML for 5G and Beyond Cybersecurity arXiv.org, (ISSN 2331-8422 ), doi: https://doi.org/10.48550/arXiv.2505.18402 , 2025. Vitenskapelig artikkel

MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data Data mining and knowledge discovery, pp. 1830 1861 , (ISSN 1384-5810 1573-756X ), doi: https://doi.org/10.1007/s10618-024-01017-y , 2024. Vitenskapelig artikkel

A comparative study of methods for estimating model-agnostic Shapley value explanations Data mining and knowledge discovery, vol. 38, pp. 1782 1829 , (ISSN 1384-5810 1573-756X ), doi: https://doi.org/10.1007/s10618-024-01016-z , 2024. Vitenskapelig artikkel

Statistiske metoder versus maskinlæringsmetoder 2024. Faglig foredrag

Hvorfor er maskinlæring nødvendig i kampen mot hvitvasking? , 2024. Programdeltagelse

Introduction to XAI 2024. Faglig foredrag

Hvordan forklarer vi kunstig intelligens 2024. Faglig foredrag

How to navigate in the Explainable AI jungle 2024. Faglig foredrag

Introduction to the 1st Oslo Invitational Workshop on Model-Agnostic Explainable AI 2024. Faglig foredrag

eXplego: An XAI-method selection tool 2024. Faglig foredrag

Forskning på ML for hvitvaskingsdeteksjon 2024. Faglig foredrag

On conditional Shapley values for prediction explanation - Adaptive & variance stabilizing estimation with KernelSHAP 2024. Poster

Recent computational advances in Shapley values based prediction explanation 2024. Vitenskapelig foredrag

More effective computation of Shapley values 2024. Vitenskapelig foredrag

Introduction to XAI 2024. Faglig foredrag

Olav Nikolai Risdal Breivik; Martin Jullum; Leveraging Norwegian Data to Improve Danish Insurance Risk Models NR-notat, 2024. Vitenskapelig artikkel

Leveraging Norwegian Data to Improve Danish Insurance Risk Models 2024. Rapport

Finetuning credit scoring ensemble models for FundingPartner 2024. Rapport

Introduksjon til sentrale metoder i statistisk modellering og maskinlæring 2023. Faglig foredrag

Some recent trends in embeddings of time series and dynamic networks Journal of Time Series Analysis, vol. 44, pp. 686 709 , (ISSN 0143-9782 1467-9892 ), doi: https://doi.org/10.1111/jtsa.12677 , 2023. Vitenskapelig artikkel

Statistical Embedding: Beyond Principal Components Statistical Science, vol. 38, pp. 411 439 , (ISSN 0883-4237 2168-8745 ), doi: https://doi.org/10.1214/22-STS881 , 2023. Vitenskapelig artikkel

Forsker tror ikke strømregningen blir mye lavere med ny støtteordning 2023. Intervju

Et forslag til strømstøtte basert på timespriser , 2023. Kronikk

Deteksjon av hvitvasking 2023. Faglig foredrag

eXplego: An interactive Tool that Helps you Select Appropriate XAI-methods for your Explainability Needs CEUR Workshop Proceedings, vol. 3554, pp. 146 151 , (ISSN 1613-0073 ), , 2023. Vitenskapelig artikkel

Why AI needs maths and stats -- lessons from working in a CS field 2023. Faglig foredrag

ML in AML - Machine Learning for Anti Money Laundering 2023. Faglig foredrag

A ridiculously simple approach to counterfactual explanations 2023. Vitenskapelig foredrag

A ridiculously simple approach to counterfactual explanations 2023. Vitenskapelig foredrag

Saldoprognoser 2022. Rapport

AI/ML for 5G and Beyond Cybersecurity 2022. Rapport

Statistical embedding: Beyond principal components 2022. Faglig foredrag

Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features Journal of machine learning research, vol. 23, pp. 1 51 , (ISSN 1532-4435 1533-7928 ), , 2022. Vitenskapelig artikkel

Prediction Explanation with Shapley values 2022. Vitenskapelig foredrag

White paper on performance evaluation of volatility estimation methods for Exabel 2021. Rapport

Efficient and simple prediction explanations with groupShapley: A practical perspective 2021. Vitenskapelig foredrag

Explaining individual predictions when features are dependent: More accurate approximations to Shapley values 2021. Vitenskapelig foredrag

Efficient Shapley value explanations through feature groups 2021. Vitenskapelig foredrag

groupShapley: Efficient prediction explanation with Shapley values for feature groups , 2021. Rapport

Whitepaper on Exabel’s Factor Model 2021. Rapport

Comparison of Contextual Importance and Utility with LIME and Shapley Values Lecture Notes in Computer Science (LNCS), vol. 12688, pp. 39 54 , (ISSN 0302-9743 1611-3349 ), doi: https://doi.org/10.1007/978-3-030-82017-6_3 , 2021. Vitenskapelig artikkel

Efficient and simple prediction explanations with groupShapley: A practical perspective CEUR Workshop Proceedings, vol. 3014, (ISSN 1613-0073 ), , 2021. Vitenskapelig artikkel

Explaining individual predictions when features are dependent: More accurate approximations to Shapley values Artificial Intelligence, vol. 298, (ISSN 0004-3702 1872-7921 ), doi: https://doi.org/10.1016/j.artint.2021.103502 , 2021. Vitenskapelig artikkel

Explaining predictive models using Shapley values and non-parametric vine copulas Dependence Modeling, vol. 9, pp. 62 81 , (ISSN 2300-2298 ), doi: https://doi.org/10.1515/demo-2021-0103 , 2021. Vitenskapelig artikkel

Explaining individual predictions when features are dependent: More accurate approximations to Shapley values 2021. Poster

groupSHAP: Efficient Shapley value explanation through feature groups 2021. Poster

shapr: An R-package for explaining machine learning models with dependence-aware Shapley values Journal of Open Source Software (JOSS), vol. 5, (ISSN 2475-9066 ), doi: https://doi.org/10.21105/joss.02027 , 2020. Vitenskapelig artikkel

How to open the black box – individual prediction explanation 2020. Vitenskapelig foredrag

Pairwise local Fisher and naive Bayes: Improving two standard discriminants Journal of Econometrics, vol. 216, pp. 284 304 , (ISSN 0304-4076 1872-6895 ), doi: https://doi.org/10.1016/j.jeconom.2020.01.019 , 2020. Vitenskapelig artikkel

Detecting money laundering transactions with machine learning Journal of Money Laundering Control, vol. 23, pp. 173 186 , (ISSN 1368-5201 1758-7808 ), doi: https://doi.org/10.1108/JMLC-07-2019-0055 , 2020. Vitenskapelig artikkel

Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling Journal of the Royal Statistical Society, Series C (Applied Statistics), vol. 69, (ISSN 0035-9254 1467-9876 ), doi: https://doi.org/10.1111/rssc.12397 , 2020. Vitenskapelig artikkel

Investigating mesh-based approximation methods for the normalization constant in the log Gaussian Cox process likelihood Stat, vol. 9, (ISSN 2049-1573 ), doi: https://doi.org/10.1002/sta4.285 , 2020. Vitenskapelig artikkel

Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees pp. 117 137 , doi: https://doi.org/10.1007/978-3-030-57321-8_7 , 2020. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Kjersti Aas; Martin Jullum; Anders Løland; Shapley explanations using conditional inference trees 2019. Rapport

Mindre rutinearbeid med maskinlæring -- Automatisk deteksjon av hvitvasking 2019. Faglig foredrag

How to open the black box -- Individual prediction explanation 2019. Vitenskapelig foredrag

Opening the black box -- individual prediction explanation 2019. Vitenskapelig foredrag

Detecting money laundering transactions – two stories 2018. Faglig foredrag

XGBoost - efficient tree boosting 2018. Faglig foredrag

Parametric or nonparametric, that’s the question 2018. Vitenskapelig foredrag

Detecting money laundering transactions -- which transactions should we learn from? 2018. Rapport

Estimating seal pup production in the Greenland Sea using Bayesian hierarchical modeling , 2018. Rapport

Estimating the seal pup abundance in the Greenland Sea with Bayesian hierarchical modeling 2017. Vitenskapelig foredrag

A focused model selection criterion for selecting among parametric and nonparametric models 2017. Vitenskapelig foredrag

Maskinlæring for vurdering av forsikringsrisiko 2017. Rapport

Bayesian modelling of cluster point process models 2017. Vitenskapelig foredrag

Statistical modeling of repertoire overlap in entire sampling spaces , 2017. Rapport

New focused approaches to topics within model selection and approximate Bayesian inversion 2016. Doktorgradsavhandling

Empirical likelihood 2016. Faglig foredrag

Bayesian AVO inversion to rock properties using a local neighborhood in a spatial prior model The Leading Edge, vol. 35, pp. 431 436 , (ISSN 1070-485X 1938-3789 ), doi: https://doi.org/10.1190/tle35050431.1 , 2016. Vitenskapelig artikkel

New focused approaches to topics within model selection and approximate Bayesian inversion 2016. Faglig foredrag

FIC with a nonparametric candidate – a new strategy for FIC construction 2016. Vitenskapelig foredrag

Estimating seal pup abundance with LGCP 2016. Vitenskapelig foredrag

An Approximate Bayesian Inversion Framework based on Local-Gaussian Likelihoods EarthDoc, doi: https://doi.org/10.3997/2214-4609.201413634 , 2015. Sammendrag/abstract

A Gaussian-based framework for local Bayesian inversion of geophysical data to rock properties Geophysics, vol. 81, pp. R75 R87 , (ISSN 0016-8033 1942-2156 ), doi: https://doi.org/10.1190/GEO2015-0314.1 , 2015. Vitenskapelig artikkel

Nils Lid Hjort; To liv: kvinnene i Lillestrøm som ble født på samme dag og døde på samme dag (FocuStat Blog Post) , 2015. Nettsider (opplysningsmateriale)

An Approximate Bayesian Inversion Framework based on Local-gaussian Likelihoods 2015. Vitenskapelig foredrag

Parametric or Nonparametric: The Focused Information Criterion Approach (+ Approximate Bayesian Inference) 2013. Vitenskapelig foredrag

Strekker Laban seg litt lengre? Forskning.no, (ISSN 1891-635X 1891-6341 ), , 2011. Populærvitenskapelig artikkel

Vindprognoser og strømpriser 2011. Rapport

Hypotesetesting av strekklengde for Seigmenn 2011. Rapport