Seniorforsker

Martin Jullum

Prosjekter

Bildet viser en grønn avfallscontainer med ulike avfallsmaterialet oppi containeren.
  • Maskinlæring

Smart avfallshåndtering med maskinlæring og radarsensorer (ReWaCC)

Publikasjoner

  • 84 publikasjoner funnet
  • Utgiver

Sandeep Pirbhulal; Habtamu Abie; Martin Jullum; Nielsen Didrik; Anders Løland; AI/ML for 5G and Beyond Cybersecurity arXiv.org, (ISSN 2331-8422 ), doi: https://doi.org/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

Martin Jullum; Kjersti Aas; Statistiske metoder versus maskinlæringsmetoder 2024. Faglig foredrag

Martin Jullum; Introduction to XAI 2024. Faglig foredrag

Martin Jullum; Hvordan forklarer vi kunstig intelligens 2024. Faglig foredrag

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

Martin Jullum; Kjersti Aas; Anders Løland; Introduction to the 1st Oslo Invitational Workshop on Model-Agnostic Explainable AI 2024. Faglig foredrag

Martin Jullum; Anders Løland; Robindra Prabhu; Jacob Sjødin; eXplego: An XAI-method selection tool 2024. Faglig foredrag

Martin Jullum; Forskning på ML for hvitvaskingsdeteksjon 2024. Faglig foredrag

Martin Jullum; Kjersti Aas; Anders Løland; Frida Svendal Aase; Lars Henry Berge Olsen; On conditional Shapley values for prediction explanation - Adaptive & variance stabilizing estimation with KernelSHAP 2024. Poster

Martin Jullum; Kjersti Aas; Frida Svendal Aase; Anders Løland; Recent computational advances in Shapley values based prediction explanation 2024. Vitenskapelig foredrag

Martin Jullum; Frida Svendal Aase; Kjersti Aas; More effective computation of Shapley values 2024. Vitenskapelig foredrag

Martin Jullum; 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

Olav Nikolai Breivik; Martin Jullum; Leveraging Norwegian Data to Improve Danish Insurance Risk Models 2024. Rapport

Utgiver Norsk Regnesentral

Martin Jullum; Kjersti Aas; Finetuning credit scoring ensemble models for FundingPartner 2024. Rapport

Utgiver Norsk Regnesentral

Solveig Engebretsen; Martin Jullum; Anders Løland; 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

Martin Jullum; Forsker tror ikke strømregningen blir mye lavere med ny støtteordning Intervju Dagens Næringsliv, 2023. Intervju tidsskrift

Martin Jullum; 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

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

Martin Jullum; Kjersti Aas; Anders Løland; Annabelle Alice Redelmeier; A ridiculously simple approach to counterfactual explanations 2023. Vitenskapelig foredrag

Martin Jullum; Kjersti Aas; Anders Løland; Annabelle Alice Redelmeier; A ridiculously simple approach to counterfactual explanations 2023. Vitenskapelig foredrag

Hanne Therese Wist Rognebakke; Kjersti Aas; Martin Jullum; Saldoprognoser 2022. Rapport

Utgiver Norsk Regnesentral

Sandeep Pirbhulal; Habtamu Abie; Martin Jullum; Didrik Nielsen; Anders Løland; AI/ML for 5G and Beyond Cybersecurity 2022. Rapport

Utgiver Norsk Regnesentral

Dag Bjarne Tjøstheim; Martin Jullum; Anders Løland; 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

Martin Jullum; Prediction Explanation with Shapley values 2022. Vitenskapelig foredrag

Øyvind Grotmol; Martin Jullum; Kjersti Aas; Michael Scheuerer; White paper on performance evaluation of volatility estimation methods for Exabel 2021. Rapport

Utgiver EXABEL

Martin Jullum; Annabelle Alice Redelmeier; Kjersti Aas; Efficient and simple prediction explanations with groupShapley: A practical perspective 2021. Vitenskapelig foredrag

Martin Jullum; Kjersti Aas; Anders Løland; Explaining individual predictions when features are dependent: More accurate approximations to Shapley values 2021. Vitenskapelig foredrag

Martin Jullum; Annabelle Alice Redelmeier; Kjersti Aas; Efficient Shapley value explanations through feature groups 2021. Vitenskapelig foredrag

Øyvind Grotmol; Michael Scheuerer; Kjersti Aas; Martin Jullum; Whitepaper on Exabel’s Factor Model 2021. Rapport

Utgiver EXABEL

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

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

Utgiver Walter de Gruyter (De Gruyter)

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

Martin Jullum; 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

Martin Jullum; Anders Løland; Ragnar Bang Huseby; Geir Ånonsen; Johannes P Lorentzen; 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

Utgiver Emerald Group Publishing Limited

Martin Jullum; Thordis Linda Thorarinsdottir; Fabian E. Bachl; Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling The Journal of the Royal Statistical Society, Series C (Applied Statistics), vol. 69, pp. 0 , (ISSN 0035-9254 1467-9876 ), doi: https://doi.org/10.1111/rssc.12397 , 2020. Vitenskapelig artikkel

Utgiver John Wiley & Sons

Martin Jullum; Investigating mesh-based approximation methods for the normalization constant in the log Gaussian Cox process likelihood Stat, vol. 9, pp. 0 , (ISSN 2049-1573 2049-1573 ), doi: https://doi.org/10.1002/sta4.285 , 2020. Vitenskapelig artikkel

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

Utgiver Norsk Regnesentral

Martin Jullum; Lars Erik Bolstad; Mindre rutinearbeid med maskinlæring -- Automatisk deteksjon av hvitvasking 2019. Faglig foredrag

Martin Jullum; Kjersti Aas; Anders Løland; How to open the black box -- Individual prediction explanation 2019. Vitenskapelig foredrag

Martin Jullum; Kjersti Aas; Anders Løland; Opening the black box -- individual prediction explanation 2019. Vitenskapelig foredrag

Anders Løland; Martin Jullum; Ragnar Bang Huseby; Detecting money laundering transactions – two stories 2018. Faglig foredrag

Martin Jullum; XGBoost - efficient tree boosting 2018. Faglig foredrag

Martin Jullum; Nils Lid Hjort; Parametric or nonparametric, that’s the question 2018. Vitenskapelig foredrag

Martin Jullum; Anders Løland; Ragnar Bang Huseby; Geir Ånonsen; Johannes P Lorentzen; Detecting money laundering transactions -- which transactions should we learn from? 2018. Rapport

Utgiver Norsk Regnesentral

Martin Jullum; Thordis Linda Thorarinsdottir; Fabian Bachl; Estimating seal pup production in the Greenland Sea using Bayesian hierarchical modeling , 2018. Rapport

Utgiver Norsk Regnesentral

Martin Jullum; Thordis Linda Thorarinsdottir; Fabian Bachl; Estimating the seal pup abundance in the Greenland Sea with Bayesian hierarchical modeling 2017. Vitenskapelig foredrag

Kjersti Aas; Martin Jullum; Linda Reiersølmoen Neef; Maskinlæring for vurdering av forsikringsrisiko 2017. Rapport

Utgiver Norsk Regnesentral

Thordis Linda Thorarinsdottir; Martin Jullum; Peter Guttorp; Bayesian modelling of cluster point process models 2017. Vitenskapelig foredrag

Lars Holden; Martin Jullum; Geir Kjetil Sandve; Statistical modeling of repertoire overlap in entire sampling spaces , 2017. Rapport

Utgiver Norsk Regnesentral
Utgiver Faculty of Mathematics and Natural Sciences, University of Oslo

Martin Jullum; Empirical likelihood 2016. Faglig foredrag

Odd Kolbjørnsen; Arild Buland; Ragnar Hauge; Per Røe; Martin Jullum; et al. 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

Martin Jullum; Thordis Linda Thorarinsdottir; Fabian Bachl; Estimating seal pup abundance with LGCP 2016. Vitenskapelig foredrag

Martin Jullum; Odd Kolbjørnsen; An Approximate Bayesian Inversion Framework based on Local-Gaussian Likelihoods EarthDoc, pp. 4 , doi: https://doi.org/10.3997/2214-4609.201413634 , 2015. Sammendrag/abstract

Martin Jullum; Odd Kolbjørnsen; 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

Martin Jullum; Odd Kolbjørnsen; An Approximate Bayesian Inversion Framework based on Local-gaussian Likelihoods 2015. Vitenskapelig foredrag

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

Utgiver Norges forskningsråd

Martin Jullum; Vindprognoser og strømpriser 2011. Rapport

Utgiver Norsk Regnesentral

Martin Jullum; Hypotesetesting av strekklengde for Seigmenn 2011. Rapport

Utgiver Norsk Regnesentral