Discovering Dynamics. - Saso Dzeroski; Ljupco Todorovski (ICML, 1993)

Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract). - Saso Dzeroski; Ljupco Todorovski; Tanja Urbancic (ECML, 1995)

Discovering Dynamics: From Inductive Logic Programming to Machine Discovery. - Saso Dzeroski; Ljupco Todorovski (J. Intell. Inf. Syst., 1995)

Declarative Bias in Equation Discovery. - Ljupco Todorovski; Saso Dzeroski (ICML, 1997)

WWW search engine for Slovenian and English medical documents. - Jure Dimec; Saso Dzeroski; Ljupco Todorovski; Dimitar Hristovski (MIE, 1999)

Analysis of free MEDLINE on the WWW. - Eva Klemencic; Ljupco Todorovski (MIE, 1999)

Organization and dissemination of multimedia medical databases on the WWW. - Ljupco Todorovski; Samo Ribaric; Jure Dimec; Emil Hudomalj; Tomaz Lunder (MIE, 1999)

Experiments in Meta-level Learning with ILP. - Ljupco Todorovski; Saso Dzeroski (PKDD, 1999)

Equation Discovery System And Neural Networks For Short-Term Dc Voltage Prediction. - Irena Nancovska; Anton Jeglic; Dusan Fefer; Ljupco Todorovski (Informatica (Slovenia), 1999)

Discovering the Structure of Partial Differential Equations from Example Behaviour. - Ljupco Todorovski; Saso Dzeroski; Ashwin Srinivasan 001; Jonathan P. Whiteley; David Gavaghan (ICML, 2000)

Combining Multiple Models with Meta Decision Trees. - Ljupco Todorovski; Saso Dzeroski (PKDD, 2000)

Predictive Performance of Weghted Relative Accuracy. - Ljupco Todorovski; Peter A. Flach; Nada Lavrac (PKDD, 2000)

Deterministic predictive models for DC voltage reference source control. - Irena Nancovska; Anton Jeglic; Dusan Fefer; Ljupco Todorovski (IEEE Trans. Ind. Electron., 2000)

Theory Revision in Equation Discovery. - Ljupco Todorovski; Saso Dzeroski (Discovery Science, 2001)

Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery. - Ljupco Todorovski; Saso Dzeroski (ECML, 2001)

A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. - Bernard Zenko; Ljupco Todorovski; Saso Dzeroski (ICDM, 2001)

Presentation of dermatological images on the Internet. - Samo Ribaric; Ljupco Todorovski; Jure Dimec; Tomaz Lunder (Comput. Methods Programs Biomed., 2001)

Ranking with Predictive Clustering Trees. - Ljupco Todorovski; Hendrik Blockeel; Saso Dzeroski (ECML, 2002)

Adapting classification rule induction to subgroup discovery. - Nada Lavrac; Peter A. Flach; Branko Kavsek; Ljupco Todorovski (ICDM, 2002)

Inducing Process Models from Continuous Data. - Pat Langley; Javier Nicolás Sánchez; Ljupco Todorovski; Saso Dzeroski (ICML, 2002)

Using Constraints in Discovering Dynamics. - Saso Dzeroski; Ljupco Todorovski; Peter Ljubic (Discovery Science, 2003)

Modelling Soil Radon Concentration for Earthquake Prediction. - Saso Dzeroski; Ljupco Todorovski; Boris Zmazek; Janja Vaupotic; Ivan Kobal (Discovery Science, 2003)

Using Domain Specific Knowledge for Automated Modeling. - Ljupco Todorovski; Saso Dzeroski (IDA, 2003)

Inductive Databases of Polynomial Equations. - Saso Dzeroski; Ljupco Todorovski; Peter Ljubic (KDID, 2003)

Combining Classifiers with Meta Decision Trees. - Ljupco Todorovski; Saso Dzeroski (Mach. Learn., 2003)

Inductive Queries on Polynomial Equations. - Saso Dzeroski; Ljupco Todorovski; Peter Ljubic (Constraint-Based Mining and Inductive Databases, 2004)

Inducing Polynomial Equations for Regression. - Ljupco Todorovski; Peter Ljubic; Saso Dzeroski (ECML, 2004)

Integrating Knowledge-Driven and Data-Driven Approaches to Modeling. - Ljupco Todorovski; Saso Dzeroski (EnviroInfo (1), 2004)

ROC Analysis of Example Weighting in Subgroup Discovery. - Branko Kavsek; Nada Lavrac; Ljupco Todorovski (ROCAI, 2004)

Subgroup Discovery with CN2-SD. - Nada Lavrac; Branko Kavsek; Peter A. Flach; Ljupco Todorovski (J. Mach. Learn. Res., 2004)

Inducing Hierarchical Process Models in Dynamic Domains. - Ljupco Todorovski; Will Bridewell; Oren Shiran; Pat Langley (AAAI, 2005)

Reducing overfitting in process model induction. - Will Bridewell; Narges Bani Asadi; Pat Langley; Ljupco Todorovski (ICML, 2005)

Constructing explanatory process models from biological data and knowledge. - Pat Langley; Oren Shiran; Jeff Shrager; Ljupco Todorovski; Andrew Pohorille (Artif. Intell. Medicine, 2006)

Computational Discovery of Scientific Knowledge. - Saso Dzeroski; Pat Langley; Ljupco Todorovski (Computational Discovery of Scientific Knowledge, 2007)

Integrating Domain Knowledge in Equation Discovery. - Ljupco Todorovski; Saso Dzeroski (Computational Discovery of Scientific Knowledge, 2007)

Reference Models for E-Services Integration Based on Life-Events. - Ljupco Todorovski; Mateja Kunstelj; Mirko Vintar (EGOV, 2007)

Learning Declarative Bias. - Will Bridewell; Ljupco Todorovski (ILP, 2007)

Extracting constraints for process modeling. - Will Bridewell; Stuart R. Borrett; Ljupco Todorovski (K-CAP, 2007)

A Minimal Description Length Scheme for Polynomial Regression. - Aleksandar Peckov; Saso Dzeroski; Ljupco Todorovski (PAKDD, 2008)

Inductive process modeling. - Will Bridewell; Pat Langley; Ljupco Todorovski; Saso Dzeroski (Mach. Learn., 2008)

Mapping the E-Government Research with Social Network Analysis. - Nusa Erman; Ljupco Todorovski (EGOV, 2009)

The Induction and Transfer of Declarative Bias. - Will Bridewell; Ljupco Todorovski (AAAI, 2010)

Analyzing the Structure of the EGOV Conference Community. - Nusa Erman; Ljupco Todorovski (EGOV, 2010)

Equation Discovery. - Ljupco Todorovski (Encyclopedia of Machine Learning, 2010)

Inductive Process Modeling. - Ljupco Todorovski (Encyclopedia of Machine Learning, 2010)

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. - Katerina Tashkova; Peter Korosec; Jurij Silc; Ljupco Todorovski; Saso Dzeroski (BMC Syst. Biol., 2011)

Automated discovery of a model for dinoflagellate dynamics. - Natasa Atanasova; Saso Dzeroski; Boris Kompare; Ljupco Todorovski; Gideon Gal (Environ. Model. Softw., 2011)

Discovering Constraints for Inductive Process Modeling. - Ljupco Todorovski; Will Bridewell; Pat Langley (AAAI, 2012)

Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis. - Jovan Tanevski; Ljupco Todorovski; Yannis Kalaidzidis; Saso Dzeroski (Discovery Science, 2013)

Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis. - Jovan Tanevski; Ljupco Todorovski; Yannis Kalaidzidis; Saso Dzeroski (BMC Syst. Biol., 2015)

Predicting long-term population dynamics with bagging and boosting of process-based models. - Nikola Simidjievski; Ljupco Todorovski; Saso Dzeroski (Expert Syst. Appl., 2015)

The effects of measurement error in case of scientific network analysis. - Nusa Erman; Ljupco Todorovski (Scientometrics, 2015)

Learning Ensembles of Process-Based Models by Bagging of Random Library Samples. - Nikola Simidjievski; Ljupco Todorovski; Saso Dzeroski (DS, 2016)

Learning stochastic process-based models of dynamical systems from knowledge and data. - Jovan Tanevski; Ljupco Todorovski; Saso Dzeroski (BMC Syst. Biol., 2016)

General Meta-Model Framework for Surrogate-Based Numerical Optimization. - Ziga Luksic; Jovan Tanevski; Saso Dzeroski; Ljupco Todorovski (DS, 2017)

Process-Based Modeling and Design of Dynamical Systems. - Jovan Tanevski; Nikola Simidjievski; Ljupco Todorovski; Saso Dzeroski (ECML/PKDD (3), 2017)

The Influence of Feature Representation of Text on the Performance of Document Classification. - Sanda Martincic-Ipsic; Tanja Milicic; Ljupco Todorovski (CoRR, 2017)

Decoupling approximation robustly reconstructs directed dynamical networks. - Nikola Simidjievski; Jovan Tanevski; Bernard Zenko; Zoran Levnajic; Ljupco Todorovski; Saso Dzeroski (CoRR, 2017)

Equation Discovery. - Ljupco Todorovski (Encyclopedia of Machine Learning and Data Mining, 2017)

Inductive Process Modeling. - Ljupco Todorovski (Encyclopedia of Machine Learning and Data Mining, 2017)

Towards reusable process-based models of dynamical systems: A case study in the domain of aquatic ecosystems. - Ilin Tolovski; Ana Kostovska; Nikola Simidjievski; Ljupco Todorovski; Saso Dzeroski; Pance Panov (MIPRO, 2019)

Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems. - Ziga Luksic; Jovan Tanevski; Saso Dzeroski; Ljupco Todorovski (IEEE Access, 2019)

Reconstructing dynamical networks via feature ranking. - Marc G. Leguia; Zoran Levnajic; Ljupco Todorovski; Bernard Zenko (CoRR, 2019)

Assessing the Agreement in the Bebras Tasks Categorisation. - Zan Ternik; Ljupco Todorovski; Irena Nancovska Serbec (ISSEP, 2020)

Equation Discovery for Nonlinear System Identification. - Nikola Simidjievski; Ljupco Todorovski; Jus Kocijan; Saso Dzeroski (IEEE Access, 2020)

Combinatorial search for selecting the structure of models of dynamical systems with equation discovery. - Jovan Tanevski; Ljupco Todorovski; Saso Dzeroski (Eng. Appl. Artif. Intell., 2020)

Extractive Text Summarization Based on Selectivity Ranking. - Dino Aljevic; Ljupco Todorovski; Sanda Martincic-Ipsic (INISTA, 2021)

Explaining the Performance of Multi-label Classification Methods with Data Set Properties. - Jasmin Bogatinovski; Ljupco Todorovski; Saso Dzeroski; Dragi Kocev (CoRR, 2021)

Predicting Hidden Links and Missing Nodes in Scale-Free Networks with Artificial Neural Networks. - Rakib Hassan Pran; Ljupco Todorovski (CoRR, 2021)

Probabilistic grammars for equation discovery. - Jure Brence; Ljupco Todorovski; Saso Dzeroski (Knowl. Based Syst., 2021)

Discovery of Differential Equations Using Probabilistic Grammars. - Bostjan Gec; Nina Omejc; Jure Brence; Saso Dzeroski; Ljupco Todorovski (DS, 2022)

P(Expression|Grammar): Probability of deriving an algebraic expression with a probabilistic context-free grammar. - Urh Primozic; Ljupco Todorovski; Matej Petkovic (CoRR, 2022)

Comprehensive comparative study of multi-label classification methods. - Jasmin Bogatinovski; Ljupco Todorovski; Saso Dzeroski; Dragi Kocev (Expert Syst. Appl., 2022)

A Review of Digital Era Governance Research in the First Two Decades: A Bibliometric Study. - Dejan Ravselj; Lan Umek; Ljupco Todorovski; Aleksander Aristovnik (Future Internet, 2022)

Explaining the performance of multilabel classification methods with data set properties. - Jasmin Bogatinovski; Ljupco Todorovski; Saso Dzeroski; Dragi Kocev (Int. J. Intell. Syst., 2022)

MLFMF: Data Sets for Machine Learning for Mathematical Formalization. - Andrej Bauer; Matej Petkovic; Ljupco Todorovski (NeurIPS, 2023)

Dimensionally-consistent equation discovery through probabilistic attribute grammars. - Jure Brence; Saso Dzeroski; Ljupco Todorovski (Inf. Sci., 2023)

Boosting the performance of quantum annealers using machine learning. - Jure Brence; Dragan Mihailovic; Viktor V. Kabanov; Ljupco Todorovski; Saso Dzeroski; Jaka Vodeb (Quantum Mach. Intell., 2023)

Dynobench - extended Strogatz benchmark for system identification methods. - Nina Omejc; Bostjan Gec; Jure Brence; Ljupco Todorovski; Saso Dzeroski (Zenodo, 2023)

Efficient generator of mathematical expressions for symbolic regression. - Sebastian Meznar; Saso Dzeroski; Ljupco Todorovski (Mach. Learn., 2023)

Correction to: efficient generator of mathematical expressions for symbolic regression. - Sebastian Meznar; Saso Dzeroski; Ljupco Todorovski (Mach. Learn., 2023)

Quantifying Behavioural Distance Between Mathematical Expressions. - Sebastian Meznar; Saso Dzeroski; Ljupco Todorovski (CoRR, 2024)

Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data. - Nina Omejc; Bostjan Gec; Jure Brence; Ljupco Todorovski; Saso Dzeroski (Mach. Learn., 2024)

Improving stochastic models by smart denoising and latent representation optimization. - Jakob Jelencic; M. Besher Massri; Ljupco Todorovski; Marko Grobelnik; Dunja Mladenic (Inf. Sci., 2025)