Kjersti Aas

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 22

Top Topics

Predictive Model

Discriminatively Trained

Top Venues

Expert Syst. Appl.

Data Min. Knowl. Discov.

Knowl. Based Syst.

Publications

Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Discriminative multimodal learning via conditional priors in generative models. Neural Networks 169 (2024)
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
A comparative study of methods for estimating model-agnostic Shapley value explanations. Data Min. Knowl. Discov. 38 (4) (2024)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland
MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data. Data Min. Knowl. Discov. 38 (4) (2024)
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them. CoRR (2023)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Generating customer's credit behavior with deep generative models. Knowl. Based Syst. 245 (2022)
Lars H. B. Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features. J. Mach. Learn. Res. 23 (2022)
Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features. CoRR (2021)
Kjersti Aas, Thomas Nagler, Martin Jullum, Anders Løland
Explaining predictive models using Shapley values and non-parametric vine copulas. CoRR (2021)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Discriminative Multimodal Learning via Conditional Priors in Generative Models. CoRR (2021)
Kjersti Aas, Martin Jullum, Anders Løland
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. Artif. Intell. 298 (2021)
Martin Jullum, Annabelle Redelmeier, Kjersti Aas
groupShapley: Efficient prediction explanation with Shapley values for feature groups. CoRR (2021)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland
MCCE: Monte Carlo sampling of realistic counterfactual explanations. CoRR (2021)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Learning latent representations of bank customers with the Variational Autoencoder. Expert Syst. Appl. 164 (2021)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas
Explaining predictive models with mixed features using Shapley values and conditional inference trees. CoRR (2020)
Annabelle Redelmeier, Martin Jullum, Kjersti Aas
Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees. CD-MAKE (2020)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Deep generative models for reject inference in credit scoring. Knowl. Based Syst. 196 (2020)
Kjersti Aas, Martin Jullum, Anders Løland
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. CoRR (2019)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Learning Latent Representations of Bank Customers With The Variational Autoencoder. CoRR (2019)
Kjersti Aas, Hanne Rognebakke
The evolution of a mobile payment solution network. Netw. Sci. 7 (3) (2019)
Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen
Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder. CoRR (2018)
Håvard Kvamme, Nikolai Sellereite, Kjersti Aas, Steffen Sjursen
Predicting mortgage default using convolutional neural networks. Expert Syst. Appl. 102 (2018)
Ingrid Hobæk Haff, Kjersti Aas, Arnoldo Frigessi, Virginia Lacal
Structure learning in Bayesian Networks using regular vines. Comput. Stat. Data Anal. 101 (2016)
Ingrid Hobæk Haff, Kjersti Aas, Arnoldo Frigessi
On the simplified pair-copula construction - Simply useful or too simplistic? J. Multivar. Anal. 101 (5) (2010)
Kjersti Aas, Line Eikvil, Ragnar Bang Huseby
Applications of hidden Markov chains in image analysis. Pattern Recognit. 32 (4) (1999)
Kjersti Aas, Line Eikvil
Decoding bar codes from human-readable characters. Pattern Recognit. Lett. 18 (14) (1997)
Kjersti Aas, Line Eikvil, Otto Milvang
Automatic can separation. ICPR (1996)
Kjersti Aas, Line Eikvil
Text page recognition using Grey-level features and hidden Markov models. Pattern Recognit. 29 (6) (1996)
Kjersti Aas, Line Eikvil, Tove Andersen
Text Recogniton from Grey Level Images Using Hidden Markovc Models. CAIP (1995)
Line Eikvil, Kjersti Aas, Marit Holden
Tools for Automatic Recognition of Character Strings in Maps. CAIP (1995)
Line Eikvil, Kjersti Aas, Hans Koren
Tools for interactive map conversion and vectorization. ICDAR (1995)
Ragnar Bang Huseby, Gutorm Thomas Hogasen, Geir Storvik, Kjersti Aas
Combining range and intensity data with a hidden Markov model. ICPR (2) (1992)