ILP for Automated Telephony. - Filip Zelezný; Petr Miksovský; Olga Stepánková; Jirí Zídek (ILP Work-in-progress reports, 2000)

Learning Functions from Imperfect Positive Data. - Filip Zelezný (ILP, 2001)

RSD: Relational Subgroup Discovery through First-Order Feature Construction. - Nada Lavrac; Filip Zelezný; Peter A. Flach (ILP, 2002)

Lattice-Search Runtime Distributions May Be Heavy-Tailed. - Filip Zelezný; Ashwin Srinivasan 001; David Page (ILP, 2002)

A Learning System for Decision Support in Telecommunications. - Filip Zelezný; Jirí Zídgek; Olga Stepánková (Soft-Ware, 2002)

Comparative Evaluation of Approaches to Propositionalization. - Mark-A. Krogel; Simon Alan Rawles; Filip Zelezný; Peter A. Flach; Nada Lavrac; Stefan Wrobel (ILP, 2003)

Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. - Nada Lavrac; Filip Zelezný; Saso Dzeroski (Local Pattern Detection, 2004)

A Monte Carlo Study of Randomised Restarted Search in ILP. - Filip Zelezný; Ashwin Srinivasan 001; David Page (ILP, 2004)

Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. - Dragan Gamberger; Nada Lavrac; Filip Zelezný; Jakub Tolar (J. Biomed. Informatics, 2004)

Efficiency-conscious propositionalization for relational learning. - Filip Zelezný (Kybernetika, 2004)

Modelling of Agents' Behavior with Semi-collaborative Meta-agents. - Jan Tozicka; Filip Zelezný; Michal Pechoucek (CEEMAS, 2005)

An Abstract Architecture for Computational Reflection in Multi-Agent Systems. - Martin Rehák; Jan Tozicka; Michal Pechoucek; Filip Zelezný; Milan Rollo (IAT, 2005)

Efficient construction of relational features. - Filip Zelezný (ICMLA, 2005)

Efficient Sampling in Relational Feature Spaces. - Filip Zelezný (ILP, 2005)

Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. - Igor Trajkovski; Filip Zelezný; Jakub Tolar; Nada Lavrac (CompLife, 2006)

ILP Through Propositionalization and Stochastic k-Term DNF Learning. - Aline Paes; Filip Zelezný; Gerson Zaverucha; C. David Page Jr.; Ashwin Srinivasan 001 (ILP, 2006)

Relational Data Mining Applied to Virtual Engineering of Product Designs. - Monika Záková; Filip Zelezný; Javier A. García-Sedano; Cyril Masia Tissot; Nada Lavrac; Petr Kremen; Javier Molina (ILP, 2006)

Relational Descriptive Analysis of Gene Expression Data. - Igor Trajkovski; Filip Zelezný; Nada Lavrac; Jakub Tolar (STAIRS, 2006)

Propositionalization-based relational subgroup discovery with RSD. - Filip Zelezný; Nada Lavrac (Mach. Learn., 2006)

Randomised restarted search in ILP. - Filip Zelezný; Ashwin Srinivasan 001; C. David Page Jr. (Mach. Learn., 2006)

Exploiting Term, Predicate, and Feature Taxonomies in Propositionalization and Propositional Rule Learning. - Monika Záková; Filip Zelezný (ECML, 2007)

Fast estimation of first-order clause coverage through randomization and maximum likelihood. - Ondrej Kuzelka; Filip Zelezný (ICML, 2008)

Gene expression data mining guided by genomic background knowledge. - Pavel Smrz; Jana Silhavá; Jirí Kléma; Filip Zelezný (SOFSEM (2), 2008)

A Restarted Strategy for Efficient Subsumption Testing. - Ondrej Kuzelka; Filip Zelezný (Fundam. Informaticae, 2008)

Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors. - Jirí Kléma; Lenka Nováková; Filip Karel; Olga Stepánková; Filip Zelezný (IEEE Trans. Syst. Man Cybern. Part C, 2008)

Learning Relational Descriptions of Differentially Expressed Gene Groups. - Igor Trajkovski; Filip Zelezný; Nada Lavrac; Jakub Tolar (IEEE Trans. Syst. Man Cybern. Part C, 2008)

Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. - Ondrej Kuzelka; Filip Zelezný (ICML, 2009)

Integrating Multiple-Platform Expression Data through Gene Set Features. - Matej Holec; Filip Zelezný; Jirí Kléma; Jakub Tolar (ISBRA, 2009)

Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2008). - Filip Zelezný; Nada Lavrac (Mach. Learn., 2009)

Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. - Roman Barták; Ondrej Kuzelka; Filip Zelezný (Abstraction, Reformulation, and Approximation, 2010)

Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. - Roman Barták; Ondrej Kuzelka; Filip Zelezný (FLAIRS, 2010)

Speeding Up Planning through Minimal Generalizations of Partially Ordered Plans. - Radomír Cernoch; Filip Zelezný (ILP, 2010)

Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. - Ondrej Kuzelka; Filip Zelezný (ILP, 2010)

Taming the Complexity of Inductive Logic Programming. - Filip Zelezný; Ondrej Kuzelka (SOFSEM, 2010)

Gaussian logic and its applications in bioinformatics. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (BCB, 2011)

Template-based semi-automatic workflow construction for gene expression data analysis. - Jiri Belohradsky; David A. Monge; Filip Zelezný; Matej Holec; Carlos García Garino (CBMS, 2011)

Subgroup Discovery Using Bump Hunting on Multi-relational Histograms. - Radomír Cernoch; Filip Zelezný (ILP, 2011)

Satisfiability Machines. - Filip Zelezný (ILP (Late Breaking Papers), 2011)

Comparative Evaluation of Set-Level Techniques in Microarray Classification. - Jirí Kléma; Matej Holec; Filip Zelezný; Jakub Tolar (ISBRA, 2011)

Prediction of DNA-Binding Propensity of Proteins by the Ball-Histogram Method. - Andrea Szabóová; Ondrej Kuzelka; Sergio Morales E.; Filip Zelezný; Jakub Tolar (ISBRA, 2011)

Gaussian Logic for Predictive Classification. - Ondrej Kuzelka; Andrea Szabóová; Matej Holec; Filip Zelezný (ECML/PKDD (2), 2011)

Block-wise construction of tree-like relational features with monotone reducibility and redundancy. - Ondrej Kuzelka; Filip Zelezný (Mach. Learn., 2011)

An experimental test of Occam's razor in classification. - Jan Zahálka; Filip Zelezný (Mach. Learn., 2011)

Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning. - Monika Záková; Petr Kremen; Filip Zelezný; Nada Lavrac (IEEE Trans Autom. Sci. Eng., 2011)

Extending the ball-histogram method with continuous distributions and an application to prediction of DNA-binding proteins. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (BIBM, 2012)

Prediction of antimicrobial activity of peptides using relational machine learning. - Andrea Szabóová; Ondrej Kuzelka; Filip Zelezný (BIBM Workshops, 2012)

Relational Learning with Polynomials. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (ICTAI, 2012)

Bounded Least General Generalization. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (ILP, 2012)

Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (NFMCP, 2012)

Comparative evaluation of set-level techniques in predictive classification of gene expression samples. - Matej Holec; Jirí Kléma; Filip Zelezný; Jakub Tolar (BMC Bioinform., 2012)

Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search. - Andrea Szabóová; Ondrej Kuzelka; Filip Zelezný; Jakub Tolar (BMC Bioinform., 2012)

A Revised Publication Model for ECML PKDD - Hendrik Blockeel; Kristian Kersting; Siegfried Nijssen; Filip Zelezný (CoRR, 2012)

Predicting Top-k Trends on Twitter using Graphlets and Time Features. - Gustav Sourek; Ondrej Kuzelka; Filip Zelezný (ILP (Late Breaking Papers), 2013)

Formulating the template ILP consistency problem as a constraint satisfaction problem. - Roman Barták; Radomír Cernoch; Ondrej Kuzelka; Filip Zelezný (Constraints An Int. J., 2013)

Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. - Hendrik Blockeel; Kristian Kersting; Siegfried Nijssen; Filip Zelezný (Mach. Learn., 2013)

Ensemble Learning of Run-Time Prediction Models for Data-Intensive Scientific Workflows. - David A. Monge; Matej Holec; Filip Zelezný; Carlos García Garino (CARLA, 2014)

A method for reduction of examples in relational learning. - Ondrej Kuzelka; Andrea Szabóová; Filip Zelezný (J. Intell. Inf. Syst., 2014)

Guest editors introduction: special issue on Inductive Logic Programming (ILP 2012). - Fabrizio Riguzzi; Filip Zelezný (Mach. Learn., 2014)

Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. - Gustav Sourek; Ondrej Kuzelka; Filip Zelezný (AIMS, 2015)

Lifted Relational Neural Networks. - Gustav Sourek; Vojtech Aschenbrenner; Filip Zelezný; Ondrej Kuzelka (CoCo@NIPS, 2015)

Novel gene sets improve set-level classification of prokaryotic gene expression data. - Matej Holec; Ondrej Kuzelka; Filip Zelezný (BMC Bioinform., 2015)

Ensemble learning of runtime prediction models for gene-expression analysis workflows. - David A. Monge; Matej Holec; Filip Zelezný; Carlos García Garino (Clust. Comput., 2015)

Estimating Sequence Similarity from Read Sets for Clustering Sequencing Data. - Petr Rysavý; Filip Zelezný (IDA, 2016)

Learning Predictive Categories Using Lifted Relational Neural Networks. - Gustav Sourek; Suresh Manandhar; Filip Zelezný; Steven Schockaert; Ondrej Kuzelka (ILP, 2016)

Polynomial and Extensible Solutions in Lock-Chart Solving. - Radomír Cernoch; Ondrej Kuzelka; Filip Zelezný (Appl. Artif. Intell., 2016)

Estimating Sequence Similarity from Contig Sets. - Petr Rysavý; Filip Zelezný (IDA, 2017)

A First-Order Axiomatization for Transition Learning with Rich Constraints. - Jáchym Barvínek; Filip Zelezný (ILP (Late Breaking Papers), 2017)

Stacked Structure Learning for Lifted Relational Neural Networks. - Gustav Sourek; Martin Svatos; Filip Zelezný; Steven Schockaert; Ondrej Kuzelka (ILP, 2017)

Pruning Hypothesis Spaces Using Learned Domain Theories. - Martin Svatos; Gustav Sourek; Filip Zelezný; Steven Schockaert; Ondrej Kuzelka (ILP, 2017)

Lifted Relational Team Embeddings for Predictive Sports Analytics. - Ondrej Hubácek; Gustav Sourek; Filip Zelezný (ILP Up-and-Coming / Short Papers, 2018)

Deep Learning from Spatial Relations for Soccer Pass Prediction. - Ondrej Hubácek; Gustav Sourek; Filip Zelezný (MLSA@PKDD/ECML, 2018)

Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. - Gustav Sourek; Vojtech Aschenbrenner; Filip Zelezný; Steven Schockaert; Ondrej Kuzelka (J. Artif. Intell. Res., 2018)

Evaluating Model-free Directional Dependency Methods on Single-cell RNA Sequencing Data with Severe Dropout. - Eliska Dvoráková; Sajal Kumar; Jirí Kléma; Filip Zelezný; Karel Drbal; Mingzhou Song 001 (ICBRA, 2019)

Scaling up relational templated neural models. - Gustav Sourek; Filip Zelezný; Ondrej Kuzelka (NeSy@IJCAI, 2019)

Revisiting Neural-Symbolic Learning Cycle. - Martin Svatos; Gustav Sourek; Filip Zelezný (NeSy@IJCAI, 2019)

Estimating sequence similarity from read sets for clustering next-generation sequencing data. - Petr Rysavý; Filip Zelezný (Data Min. Knowl. Discov., 2019)

Learning to predict soccer results from relational data with gradient boosted trees. - Ondrej Hubácek; Gustav Sourek; Filip Zelezný (Mach. Learn., 2019)

Efficient Extraction of Network Event Types from NetFlows. - Gustav Sourek; Filip Zelezný (Secur. Commun. Networks, 2019)

Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator. - Frantisek Malinka; Filip Zelezný; Jirí Kléma (BioData Min., 2020)

Lossless Compression of Structured Convolutional Models via Lifting. - Gustav Sourek; Filip Zelezný (CoRR, 2020)

Learning with Molecules beyond Graph Neural Networks. - Gustav Sourek; Filip Zelezný; Ondrej Kuzelka (CoRR, 2020)

Guest editors' introduction: special issue on Inductive Logic Programming (ILP 2019). - Dimitar Kazakov; Filip Zelezný (Mach. Learn., 2020)

Lossless Compression of Structured Convolutional Models via Lifting. - Gustav Sourek; Filip Zelezný; Ondrej Kuzelka (ICLR, 2021)

Automatic Conjecturing of P-Recursions Using Lifted Inference. - Jáchym Barvínek; Timothy van Bremen; Yuyi Wang 001; Filip Zelezný; Ondrej Kuzelka (ILP, 2021)

Optimal sports betting strategies in practice: an experimental review. - Matej Uhrín; Gustav Sourek; Ondrej Hubácek; Filip Zelezný (CoRR, 2021)

Beyond graph neural networks with lifted relational neural networks. - Gustav Sourek; Filip Zelezný; Ondrej Kuzelka (Mach. Learn., 2021)

Lifted Relational Neural Networks: From Graphs to Deep Relational Learning. - Gustav Sír; Filip Zelezný; Ondrej Kuzelka (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Reference-free phylogeny from sequencing data. - Petr Rysavý; Filip Zelezný (BioData Min., 2023)

An Algorithm to Calculate the p-Value of the Monge-Elkan Distance. - Petr Rysavý; Filip Zelezný (J. Comput. Biol., 2025)