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2020 – today
- 2024
[j15]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): 1782-1829 (2024)- [j14]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): 1830-1861 (2024) - [j13]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Discriminative multimodal learning via conditional priors in generative models. Neural Networks 169: 417-430 (2024) - 2023
- [i10]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 abs/2305.09536 (2023) - 2022
- [j12]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: 213:1-213:51 (2022) - [j11]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Generating customer's credit behavior with deep generative models. Knowl. Based Syst. 245: 108568 (2022) - 2021
- [j10]Kjersti Aas, Martin Jullum, Anders Løland:
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. Artif. Intell. 298: 103502 (2021) - [j9]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Learning latent representations of bank customers with the Variational Autoencoder. Expert Syst. Appl. 164: 114020 (2021) - [i9]Kjersti Aas, Thomas Nagler, Martin Jullum, Anders Løland:
Explaining predictive models using Shapley values and non-parametric vine copulas. CoRR abs/2102.06416 (2021) - [i8]Martin Jullum, Annabelle Redelmeier, Kjersti Aas:
groupShapley: Efficient prediction explanation with Shapley values for feature groups. CoRR abs/2106.12228 (2021) - [i7]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Discriminative Multimodal Learning via Conditional Priors in Generative Models. CoRR abs/2110.04616 (2021) - [i6]Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland:
MCCE: Monte Carlo sampling of realistic counterfactual explanations. CoRR abs/2111.09790 (2021) - [i5]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 abs/2111.13507 (2021) - 2020
- [j8]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Deep generative models for reject inference in credit scoring. Knowl. Based Syst. 196: 105758 (2020) - [c6]Annabelle Redelmeier, Martin Jullum, Kjersti Aas:
Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees. CD-MAKE 2020: 117-137 - [i4]Annabelle Redelmeier, Martin Jullum, Kjersti Aas:
Explaining predictive models with mixed features using Shapley values and conditional inference trees. CoRR abs/2007.01027 (2020)
2010 – 2019
- 2019
- [j7]Kjersti Aas, Hanne Rognebakke:
The evolution of a mobile payment solution network. Netw. Sci. 7(3): 422-437 (2019) - [i3]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Learning Latent Representations of Bank Customers With The Variational Autoencoder. CoRR abs/1903.06580 (2019) - [i2]Kjersti Aas, Martin Jullum, Anders Løland:
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values. CoRR abs/1903.10464 (2019) - 2018
- [j6]Håvard Kvamme, Nikolai Sellereite, Kjersti Aas, Steffen Sjursen:
Predicting mortgage default using convolutional neural networks. Expert Syst. Appl. 102: 207-217 (2018) - [i1]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder. CoRR abs/1806.02538 (2018) - 2016
- [j5]Ingrid Hobæk Haff, Kjersti Aas, Arnoldo Frigessi, Virginia Lacal:
Structure learning in Bayesian Networks using regular vines. Comput. Stat. Data Anal. 101: 186-208 (2016) - 2010
- [j4]Ingrid Hobæk Haff, Kjersti Aas, Arnoldo Frigessi:
On the simplified pair-copula construction - Simply useful or too simplistic? J. Multivar. Anal. 101(5): 1296-1310 (2010)
1990 – 1999
- 1999
- [j3]Kjersti Aas, Line Eikvil, Ragnar Bang Huseby:
Applications of hidden Markov chains in image analysis. Pattern Recognit. 32(4): 703-713 (1999) - 1997
- [j2]Kjersti Aas, Line Eikvil:
Decoding bar codes from human-readable characters. Pattern Recognit. Lett. 18(14): 1519-1527 (1997) - 1996
- [j1]Kjersti Aas, Line Eikvil:
Text page recognition using Grey-level features and hidden Markov models. Pattern Recognit. 29(6): 977-985 (1996) - [c5]Kjersti Aas, Line Eikvil, Otto Milvang:
Automatic can separation. ICPR 1996: 954-958 - 1995
- [c4]Kjersti Aas, Line Eikvil, Tove Andersen:
Text Recogniton from Grey Level Images Using Hidden Markovc Models. CAIP 1995: 503-508 - [c3]Line Eikvil, Kjersti Aas, Marit Holden:
Tools for Automatic Recognition of Character Strings in Maps. CAIP 1995: 741-746 - [c2]Line Eikvil, Kjersti Aas, Hans Koren:
Tools for interactive map conversion and vectorization. ICDAR 1995: 927-930 - 1992
- [c1]Ragnar Bang Huseby, Gutorm Thomas Hogasen, Geir Storvik, Kjersti Aas:
Combining range and intensity data with a hidden Markov model. ICPR (2) 1992: 128-131
Coauthor Index
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last updated on 2024-10-07 21:24 CEST by the dblp team
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