Ingrid Kristine Glad

Ingrid Kristine Glad

Universitetet i Oslo

H-index: 21

Europe-Norway

About Ingrid Kristine Glad

Ingrid Kristine Glad, With an exceptional h-index of 21 and a recent h-index of 15 (since 2020), a distinguished researcher at Universitetet i Oslo, specializes in the field of Statistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Efficient sparsity adaptive changepoint estimation

A comparative study of methods for estimating conditional Shapley values and when to use them

A novel semi-supervised learning approach for State of Health monitoring of maritime lithium-ion batteries

Estimating the effect of biofouling on ship shaft power based on sensor measurements

A novel semi-supervised learning approach for maritime lithium-ion battery monitoring

Using Shapley values and variational autoencoders to explain predictive models with dependent mixed features

Shapley values for cluster importance: How clusters of the training data affect a prediction

Multivariable fractional polynomials for lithium-ion batteries degradation models under dynamic conditions

Ingrid Kristine Glad Information

University

Position

Professor of Statistics

Citations(all)

1947

Citations(since 2020)

634

Cited By

1532

hIndex(all)

21

hIndex(since 2020)

15

i10Index(all)

34

i10Index(since 2020)

21

Email

University Profile Page

Universitetet i Oslo

Google Scholar

View Google Scholar Profile

Ingrid Kristine Glad Skills & Research Interests

Statistics

Top articles of Ingrid Kristine Glad

Title

Journal

Author(s)

Publication Date

Efficient sparsity adaptive changepoint estimation

arXiv preprint arXiv:2306.04702

Per August Jarval Moen

Ingrid Kristine Glad

Martin Tveten

2023/6/7

A comparative study of methods for estimating conditional Shapley values and when to use them

arXiv preprint arXiv:2305.09536

Lars Henry Berge Olsen

Ingrid Kristine Glad

Martin Jullum

Kjersti Aas

2023/5/16

A novel semi-supervised learning approach for State of Health monitoring of maritime lithium-ion batteries

Journal of Power Sources

Clara Bertinelli Salucci

Azzeddine Bakdi

Ingrid Kristine Glad

Erik Vanem

Riccardo De Bin

2023/2/1

Estimating the effect of biofouling on ship shaft power based on sensor measurements

Ship Technology Research

Haakon Bakka

Hanne Rognebakke

Ingrid Glad

Ingrid Hobæk Haff

Erik Vanem

2023/9/2

A novel semi-supervised learning approach for maritime lithium-ion battery monitoring

Clara Bertinelli Salucci

Azzeddine Bakdi

Ingrid Kristine Glad

Erik Vanem

Riccardo De Bin

2022

Using Shapley values and variational autoencoders to explain predictive models with dependent mixed features

Journal of machine learning research

Lars HB Olsen

Ingrid K Glad

Martin Jullum

Kjersti Aas

2022

Shapley values for cluster importance: How clusters of the training data affect a prediction

Data Mining and Knowledge Discovery

Andreas Brandsæter

Ingrid K Glad

2022/12/6

Multivariable fractional polynomials for lithium-ion batteries degradation models under dynamic conditions

Journal of Energy Storage

Clara Bertinelli Salucci

Azzeddine Bakdi

Ingrid Kristine Glad

Erik Vanem

Riccardo De Bin

2022/8/15

Scalable change and anomaly detection in cross-correlated data

Martin Tveten

Ingrid Kristine Glad

Nils Lid Hjort

2021

Tailored graphical lasso for data integration in gene network reconstruction

BMC bioinformatics

Camilla Lingjærde

Tonje G Lien

Ørnulf Borgan

Helga Bergholtz

Ingrid K Glad

2021/12

Testbed scenario design exploiting traffic big data for autonomous ship trials under multiple conflicts with collision/grounding risks and spatio-temporal dependencies

IEEE Transactions on Intelligent Transportation Systems

Azzeddine Bakdi

Ingrid Kristine Glad

Erik Vanem

2021/12

Simple statistical models and sequential deep learning for lithium-ion batteries degradation under dynamic conditions: Fractional polynomials vs neural networks

arXiv preprint arXiv:2102.08111

Clara B Salucci

Azzeddine Bakdi

Ingrid Kristine Glad

Erik Vanem

Riccardo De Bin

2021/2

Explainable artificial intelligence: How subsets of the training data affect a prediction

stat

Andreas Brandsætera

Ingrid K Gladb

2020/12

Partially linear monotone methods with automatic variable selection and monotonicity direction discovery

Statistics in Medicine

Solveig Engebretsen

Ingrid K Glad

2020/11/10

Beware the Jaccard: the choice of similarity measure is important and non-trivial in genomic colocalisation analysis

Stefania Salvatore

Knut Dagestad Rand

Ivar Grytten

Egil Ferkingstad

Diana Domanska

...

2020/9

See List of Professors in Ingrid Kristine Glad University(Universitetet i Oslo)