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

Artificial intelligence, 2021-09, Vol.298, p.103502, Article 103502

2021

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Explaining predictive models using Shapley values and non-parametric vine copulas

Dependence modeling, 2021-06, Vol.9 (1), p.62-81

2021

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Investigating mesh‐based approximation methods for the normalization constant in the log Gaussian Cox process likelihood

Stat (International Statistical Institute), 2020, Vol.9 (1), p.n/a

Jullum, Martin

2020

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What price semiparametric Cox regression?

Lifetime data analysis, 2019-07, Vol.25 (3), p.406-438

2019

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A Gaussian-based framework for local Bayesian inversion of geophysical data to rock properties

Geophysics, 2016-05, Vol.81 (3), p.R75-R87

2016

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MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data

Data mining and knowledge discovery, 2024-07, Vol.38 (4), p.1830-1861

2024

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Statistical Embedding: Beyond Principal Components

Statistical science, 2023-08, Vol.38 (3), p.411

2023

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Pairwise local Fisher and naive Bayes: Improving two standard discriminants

Journal of econometrics, 2020-05, Vol.216 (1), p.284-304

2020

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PARAMETRIC OR NONPARAMETRIC: THE FIC APPROACH

Statistica Sinica, 2017-07, Vol.27 (3), p.951-981

2017

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Some recent trends in embeddings of time series and dynamic networks

Journal of time series analysis, 2023-09, Vol.44 (5-6), p.686-709

2023

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A comparative study of methods for estimating model-agnostic Shapley value explanations

Data mining and knowledge discovery, 2024-07, Vol.38 (4), p.1782-1829

2024

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Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features

Journal of machine learning research, 2022-01

2022

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shapr: An R-package for explaining machine learning models with dependence-aware Shapley values

Journal of open source software, 2019-02, Vol.5 (46), p.2027

2019

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Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling

Journal of the Royal Statistical Society Series C: Applied Statistics, 2020-04, Vol.69 (2), p.327-352

2020

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Detecting money laundering transactions with machine learning

Journal of money laundering control, 2020-01, Vol.23 (1), p.173-186

2020

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Comparison of Contextual Importance and Utility with LIME and Shapley Values

Explainable and Transparent AI and Multi-Agent Systems, 2021, p.39-54

2021

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Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees

Machine Learning and Knowledge Extraction, 2020, Vol.12279, p.117-137

2020

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Bayesian AVO inversion to rock properties using a local neighborhood in a spatial prior model

Leading edge (Tulsa, Okla.), 2016-05, Vol.35 (5), p.431-436

2016

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Arthroscopic partial meniscectomy versus exercise therapy for degenerative meniscal tears: 10-year follow-up of the OMEX randomised controlled trial

British journal of sports medicine, 2024-09, p.bjsports-2024-108644

2024

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

Explaining predictive models using Shapley values and non-parametric vine copulas

Investigating mesh‐based approximation methods for the normalization constant in the log Gaussian Cox process likelihood

What price semiparametric Cox regression?

A Gaussian-based framework for local Bayesian inversion of geophysical data to rock properties

MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data

Statistical Embedding: Beyond Principal Components

Pairwise local Fisher and naive Bayes: Improving two standard discriminants

PARAMETRIC OR NONPARAMETRIC: THE FIC APPROACH

Some recent trends in embeddings of time series and dynamic networks

A comparative study of methods for estimating model-agnostic Shapley value explanations

Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features

shapr: An R-package for explaining machine learning models with dependence-aware Shapley values

Estimating seal pup production in the Greenland Sea by using Bayesian hierarchical modelling

Detecting money laundering transactions with machine learning

Comparison of Contextual Importance and Utility with LIME and Shapley Values

Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees

Bayesian AVO inversion to rock properties using a local neighborhood in a spatial prior model

Arthroscopic partial meniscectomy versus exercise therapy for degenerative meniscal tears: 10-year follow-up of the OMEX randomised controlled trial

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