Isak Samsten

According to our database1, Isak Samsten authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Glacier: guided locally constrained counterfactual explanations for time series classification.
Mach. Learn., July, 2024

Castor: Competing shapelets for fast and accurate time series classification.
CoRR, 2024

COMET: Constrained Counterfactual Explanations for Patient Glucose Multivariate Forecasting.
Proceedings of the 37th IEEE International Symposium on Computer-Based Medical Systems, 2024

2023
Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients.
Artif. Intell. Medicine, January, 2023

Code quality assessment using transformers.
CoRR, 2023

Distributional Data Augmentation Methods for Low Resource Language.
CoRR, 2023

Counterfactual Explanations for Time Series Forecasting.
Proceedings of the IEEE International Conference on Data Mining, 2023

2022
Post Hoc Explainability for Time Series Classification: Toward a signal processing perspective.
IEEE Signal Process. Mag., 2022

Corporate governance performance ratings with machine learning.
Intell. Syst. Account. Finance Manag., 2022

2021
Learning Time Series Counterfactuals via Latent Space Representations.
Proceedings of the Discovery Science - 24th International Conference, 2021

Assessing the Clinical Validity of Attention-based and SHAP Temporal Explanations for Adverse Drug Event Predictions.
Proceedings of the 34th IEEE International Symposium on Computer-Based Medical Systems, 2021

Counterfactual Explanations for Survival Prediction of Cardiovascular ICU Patients.
Proceedings of the Artificial Intelligence in Medicine, 2021

2020
Exploiting complex medical data with interpretable deep learning for adverse drug event prediction.
Artif. Intell. Medicine, 2020

2019
Example-Based Feature Tweaking Using Random Forests.
Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019


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