Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention
Nagy, M., & Molontay, R. (2023)
International Journal of Artificial Intelligence in Education, Springer
Towards a better understanding of the characteristics of fractal networks
Zakar-Polyák, E., Nagy, M., & Molontay, R. (2023)
Applied Network Science, 8, 17, Springer
Network classification-based structural analysis of real
networks and their model-generated counterparts
Nagy, M. & Molontay, R. (2022)
Network Science 1-24
How to improve the predictive validity of a composite admission score?
A case study from Hungary
Molontay, R., & Nagy, M. (2022)
Assessment & Evaluation in Higher Education, 1-19
Comparative analysis of box-covering algorithms for fractal networks
Kovács, P.T., Nagy, M. & Molontay, R. (2021)
Applied Network Science 6, 73, Springer
Comprehensive analysis of the predictive validity of the university entrance score in Hungary
Nagy, M. & Molontay, R.
Assessment & Evaluation in Higher Education 1-19.
2021
Interpretable Deep Learning for University Dropout Prediction
Baranyi, M., Nagy, M., & Molontay, R.
Proceedings of the 21st Annual Conference on Information Technology Education
ACM, 2020
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