| Financial distress prediction for small and medium enterprises using machine learning techniques A Malakauskas, A Lakštutienė Engineering Economics 32 (1), 4-14, 2021 | 54 | 2021 |
| Interpretable machine learning for SME financial distress prediction K Medianovskyi, A Malakauskas, A Lakstutiene, SB Yahia International Conference on Computing and Information Technology, 454-464, 2022 | 3 | 2022 |
| Dominance tracking index for measuring pension fund performance with respect to the benchmark M Kopa, K Sutiene, A Kabasinskas, A Lakstutiene, A Malakauskas Sustainability 14 (15), 9532, 2022 | 2 | 2022 |
| The Application of Artificial Intelligence Tools in Creditworthiness Modelling for SME Entities A Malakauskas, A Lakstutiene 2021 IEEE International Conference on Technology and Entrepreneurship (ICTE …, 2021 | 2 | 2021 |
| Modelling credit rating outlook for sme entities in the Baltic states A Malakauskas ISM University of Management and Economics, 2017 | 1 | 2017 |
| Performance Evaluation of Lithuanian II Pillar Pension Funds Using Rolling Window Technique A Kabašinskas, M Kopa, K Šutienė, A Lakštutienė, A Malakauskas | 1 | |
| Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs K Medianovskyi, A Malakauskas, A Lakstutiene, SB Yahia Procedia Computer Science 225, 2163-2172, 2023 | | 2023 |
| The evaluation of access to credit for small and medium enterprises A Malakauskas Kauno technologijos universitetas, 2023 | | 2023 |
| CREDIT ACCESSIBILITY EVALUATION MODEL FOR SMALL AND MEDIUM ENTERPRISES A Malakauskas, A Lakstutiene, K Malakauskiene Finance, Economics and Tourism-FET 2022 22, 347, 2022 | | 2022 |
| Measurement of performance of Lithuanian II pillar pension funds using benchmark and rolling window technique A Kabašinskas, M Kopa, K Šutienė, A Lakštutienė, A Malakauskas DAMSS 2022: 13th conference on data analysis methods for software systems …, 2022 | | 2022 |
