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A. Sharif and D. Marijan

ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events

IEEE Transactions on Software Engineering (TSE) (2023).
Journal Article
2023
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P. M. Ness, D. Marijan and S. Bose

Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models

In ACM International Conference on Information and Knowledge Management, 2023.
Proceedings, refereed
2023
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B. Zaman, D. Altan, D. Marijan and T. Kholodna

Reactive buffering window trajectory segmentation: RBW-TS

Journal of Big Data 10 (2023).
Journal Article
2023
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D. Marijan

Comparative study of machine learning test case prioritization for continuous integration testing

Software Quality Journal (2023).
Journal Article
2023
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27 September 2023

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2023

Journal articles

D. Altan, D. Marijan and T. Kholodna

SafeWay: Improving the Safety of Autonomous Waypoint Detection in Maritime using Transformer and Interpolation

Maritime Transport Research 4 (2023).
Status: Published
M. S. Arbabi, C. Lal, N. R. Veeraragavan, D. Marijan, J. F. Nygård and R. Vitenberg

A Survey on Blockchain for Healthcare: Challenges, Benefits, and Future Directions

IEEE Communications Surveys & Tutorials 25, no. 1 (2023): 386-424.
Status: Published
D. Marijan

Comparative study of machine learning test case prioritization for continuous integration testing

Software Quality Journal (2023).
Status: Published
A. Sharif and D. Marijan

ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events

IEEE Transactions on Software Engineering (TSE) (2023).
Status: Submitted
B. Zaman, D. Marijan and T. Kholodna

Interpolation-Based Inference of Vessel Trajectory Waypoints from Sparse AIS Data in Maritime

Journal of Marine Science and Engineering 11, no. 3 (2023).
Status: Published
B. Zaman, D. Altan, D. Marijan and T. Kholodna

Reactive buffering window trajectory segmentation: RBW-TS

Journal of Big Data 10 (2023).
Status: Published

Proceedings, refereed

P. M. Ness, D. Marijan and S. Bose

Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models

In ACM International Conference on Information and Knowledge Management, 2023.
Status: Accepted