| Accurate models for P-gp drug recognition induced from a cancer cell line cytotoxicity screen J Levatić, J Ćurak, M Kralj, T Šmuc, M Osmak, F Supek Journal of medicinal chemistry 56 (14), 5691-5708, 2013 | 46 | 2013 |
| The importance of the label hierarchy in hierarchical multi-label classification J Levatić, D Kocev, S Džeroski Journal of Intelligent Information Systems 45 (2), 247-271, 2015 | 38 | 2015 |
| Self-training for multi-target regression with tree ensembles J Levatić, M Ceci, D Kocev, S Džeroski Knowledge-based systems 123, 41-60, 2017 | 31 | 2017 |
| Semi-supervised trees for multi-target regression J Levatić, D Kocev, M Ceci, S Džeroski Information Sciences 450, 109-127, 2018 | 22 | 2018 |
| Semi-supervised classification trees J Levatić, M Ceci, D Kocev, S Džeroski Journal of Intelligent Information Systems 49 (3), 461-486, 2017 | 21 | 2017 |
| Semi-supervised learning for multi-target regression J Levatic, M Ceci, D Kocev, S Dzeroski | 20 | 2014 |
| Semi-supervised learning for quantitative structure-activity modeling J Levatić, S Džeroski, F Supek, T Šmuc Informatica 37 (2), 2013 | 18 | 2013 |
| Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity J Levatić, K Pavić, I Perković, L Uzelac, K Ester, M Kralj, M Kaiser, ... European journal of medicinal chemistry 146, 651-667, 2018 | 12 | 2018 |
| Predicting thermal power consumption of the Mars Express satellite with machine learning M Breskvar, D Kocev, J Levatić, A Osojnik, M Petković, N Simidjievski, ... 2017 6th International conference on space mission challenges for …, 2017 | 12 | 2017 |
| Community structure models are improved by exploiting taxonomic rank with predictive clustering trees J Levatić, D Kocev, M Debeljak, S Džeroski Ecological modelling 306, 294-304, 2015 | 9 | 2015 |
| Machine learning for predicting thermal power consumption of the Mars Express Spacecraft M Petković, R Boumghar, M Breskvar, S Džeroski, D Kocev, J Levatić, ... IEEE Aerospace and Electronic Systems Magazine 34 (7), 46-60, 2019 | 4 | 2019 |
| The use of the label hierarchy in hierarchical multi-label classification improves performance J Levatić, D Kocev, S Džeroski International Workshop on New Frontiers in Mining Complex Patterns, 162-177, 2013 | 3 | 2013 |
| The use of the label hierarchy in HMC improves performance: A case study in predicting community structure in ecology J Levatic, D Kocev, S Dzeroski | 3 | 2013 |
| Phenotype prediction with semi-supervised learning J Levatic, M Brbic, T Perdih, D Kocev, V Vidulin, T Šmuc, F Supek, ... Proceedings of the New Frontiers in Mining Complex Patterns: Sixth Edition …, 2017 | 2 | 2017 |
| Semi-supervised regression trees with application to QSAR modelling J Levatić, M Ceci, T Stepišnik, S Džeroski, D Kocev Expert Systems with Applications, 113569, 2020 | 1 | 2020 |
| QSAR based synthesis of novel primaquine ureidoamides K Pavić, J Levatić, F Supek, B Zorc 25th Croatian Meeting of Chemists and Chemical Engineers, 2017 | 1 | 2017 |
| Phenotype Prediction with Semi-supervised Classification Trees J Levatić, M Brbić, TS Perdih, D Kocev, V Vidulin, T Šmuc, F Supek, ... International Workshop on New Frontiers in Mining Complex Patterns, 138-150, 2017 | | 2017 |
| Semi-supervised Learning for Structred Output Prediction: Doctoral Dissertation J Levatić J. Levatić, 2017 | | 2017 |
| Antimalarial screening of primaquine derivatives against erythrocytic stage of P. falciparum B Zorc, K Pavić, F Supek, J Levatić, M Kaiser Book of Abstracts, 248, 2017 | | 2017 |
| SEMI-SUPERVISED LEARNING IN DIVERSE QUANTITATIVE STRUCTURE-ACTIVITY MODELING PROBLEMS J Levatić, S Džeroski, F Supek, T Šmuc INFORMACIJSKA DRUŽBA− IS 2012, 2012 | | 2012 |
Saso DzeroskiJozef Stefan Institute, Dept. of Knowledge TechnologiesVerified email at ijs.si
