Ondrej Kuzelka

According to our database, Ondrej Kuzelka authored at least 75 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Faster Repeated Evasion Attacks in Tree Ensembles.

Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis

CoRR, 2024

2023

Lifted inference with tree axioms.

Timothy van Bremen, Ondrej Kuzelka

Artif. Intell., November, 2023

Lifted Relational Neural Networks: From Graphs to Deep Relational Learning.

Gustav Sír, Filip Zelezný, Ondrej Kuzelka

Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs.

Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt

J. Artif. Intell. Res., 2023

Lifted Algorithms for Symmetric Weighted First-Order Model Sampling.

Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka

CoRR, 2023

On Exact Sampling in the Two-Variable Fragment of First-Order Logic.

Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka

LICS, 2023

On Discovering Interesting Combinatorial Integer Sequences.

Martin Svatos, Peter Jung, Jan Tóth, Yuyi Wang, Ondrej Kuzelka

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Counting and Sampling Models in First-Order Logic.

Ondrej Kuzelka

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Lifted Inference with Linear Order Axiom.

Jan Tóth, Ondrej Kuzelka

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning Distributional Programs for Relational Autocompletion.

Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt

Theory Pract. Log. Program., 2022

Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions.

Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Beyond graph neural networks with lifted relational neural networks.

Gustav Sourek, Filip Zelezný, Ondrej Kuzelka

Mach. Learn., 2021

Weighted First-Order Model Counting in the Two-Variable Fragment With Counting Quantifiers.

Ondrej Kuzelka

J. Artif. Intell. Res., 2021

Neural markov logic networks.

Giuseppe Marra, Ondrej Kuzelka

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Faster lifting for two-variable logic using cell graphs.

Timothy van Bremen, Ondrej Kuzelka

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Automatic Conjecturing of P-Recursions Using Lifted Inference.

Jáchym Barvínek, Timothy van Bremen, Yuyi Wang, Filip Zelezný, Ondrej Kuzelka

Proceedings of the Inductive Logic Programming - 30th International Conference, 2021

Fast Algorithms for Relational Marginal Polytopes.

Yuanhong Wang, Timothy van Bremen, Juhua Pu, Yuyi Wang, Ondrej Kuzelka

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Lossless Compression of Structured Convolutional Models via Lifting.

Gustav Sourek, Filip Zelezný, Ondrej Kuzelka

Proceedings of the 9th International Conference on Learning Representations, 2021

Context-Specific Likelihood Weighting.

Nitesh Kumar, Ondrej Kuzelka

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Learning with Molecules beyond Graph Neural Networks.

Gustav Sourek, Filip Zelezný, Ondrej Kuzelka

CoRR, 2020

Lifted Inference in 2-Variable Markov Logic Networks with Function and Cardinality Constraints Using Discrete Fourier Transform.

Ondrej Kuzelka

CoRR, 2020

Markov Logic Networks with Complex Weights: Expressivity, Liftability and Fourier Transforms.

Ondrej Kuzelka

CoRR, 2020

Complex Markov Logic Networks: Expressivity and Liftability.

Ondrej Kuzelka

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Lifted Weight Learning of Markov Logic Networks (Revisited One More Time).

Ondrej Kuzelka, Vyacheslav Kungurtsev, Yuyi Wang

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry.

Timothy van Bremen, Ondrej Kuzelka

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment.

Martin Svatos, Steven Schockaert, Jesse Davis, Ondrej Kuzelka

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Domain-Liftability of Relational Marginal Polytopes.

Ondrej Kuzelka, Yuyi Wang

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption.

Ondrej Kuzelka, Jesse Davis

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Scaling up relational templated neural models.

Gustav Sourek, Filip Zelezný, Ondrej Kuzelka

Proceedings of the 2019 International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2019), 2019

Scalable Rule Learning in Probabilistic Knowledge Bases.

Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt

Proceedings of the 1st Conference on Automated Knowledge Base Construction, 2019

Lifted Weight Learning of Markov Logic Networks Revisited.

Ondrej Kuzelka, Vyacheslav Kungurtsev

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

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

Markov Logic Networks with Statistical Quantifiers.

Víctor Gutiérrez-Basulto, Jean Christoph Jung, Ondrej Kuzelka

CoRR, 2018

PAC-Reasoning in Relational Domains.

Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

VC-Dimension Based Generalization Bounds for Relational Learning.

Ondrej Kuzelka, Yuyi Wang, Steven Schockaert

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Quantified Markov Logic Networks.

Víctor Gutiérrez-Basulto, Jean Christoph Jung, Ondrej Kuzelka

Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Sixteenth International Conference, 2018

Modelling Salient Features as Directions in Fine-Tuned Semantic Spaces.

Thomas Ager, Ondrej Kuzelka, Steven Schockaert

Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018

Relational Marginal Problems: Theory and Estimation.

Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Pruning Hypothesis Spaces Using Learned Domain Theories.

Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka

Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Stacked Structure Learning for Lifted Relational Neural Networks.

Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka

Proceedings of the Inductive Logic Programming - 27th International Conference, 2017

Induction of Interpretable Possibilistic Logic Theories from Relational Data.

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract).

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

CoRR, 2016

Polynomial and Extensible Solutions in Lock-Chart Solving.

Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný

Appl. Artif. Intell., 2016

Inducing Symbolic Rules from Entity Embeddings using Auto-encoders.

Thomas Ager, Ondrej Kuzelka, Steven Schockaert

Proceedings of the 11th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'16) co-located with the Joint Multi-Conference on Human-Level Artificial Intelligence (HLAI 2016), 2016

Learning Predictive Categories Using Lifted Relational Neural Networks.

Gustav Sourek, Suresh Manandhar, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka

Proceedings of the Inductive Logic Programming - 26th International Conference, 2016

Bounds for Learning from Evolutionary-Related Data in the Realizable Case.

Ondrej Kuzelka, Yuyi Wang, Jan Ramon

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning Possibilistic Logic Theories from Default Rules.

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Interpretable Encoding of Densities Using Possibilistic Logic.

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

2015

Novel gene sets improve set-level classification of prokaryotic gene expression data.

Matej Holec, Ondrej Kuzelka, Filip Zelezný

BMC Bioinform., 2015

Encoding Markov logic networks in Possibilistic Logic.

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Lifted Relational Neural Networks.

Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka

Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), 2015

A Note on Restricted Forms of LGG.

Ondrej Kuzelka, Jan Ramon

Proceedings of the Late Breaking Papers of the 25th International Conference on Inductive Logic Programming, 2015

Mine 'Em All: A Note on Mining All Graphs.

Ondrej Kuzelka, Jan Ramon

Proceedings of the Inductive Logic Programming - 25th International Conference, 2015

Constructing Markov Logic Networks from First-Order Default Rules.

Ondrej Kuzelka, Jesse Davis, Steven Schockaert

Proceedings of the Inductive Logic Programming - 25th International Conference, 2015

Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic.

Gustav Sourek, Ondrej Kuzelka, Filip Zelezný

Proceedings of the Intelligent Mechanisms for Network Configuration and Security, 2015

2014

A method for reduction of examples in relational learning.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

J. Intell. Inf. Syst., 2014

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

Predicting Top-k Trends on Twitter using Graphlets and Time Features.

Gustav Sourek, Ondrej Kuzelka, Filip Zelezný

Proceedings of the Late Breaking Papers of the 23rd International Conference on Inductive Logic Programming, Rio de Janeiro, Brazil, August 28th - to, 2013

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

Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

Proceedings of the New Frontiers in Mining Complex Patterns - First International Workshop, 2012

Bounded Least General Generalization.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

Proceedings of the Inductive Logic Programming - 22nd International Conference, 2012

Relational Learning with Polynomials.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

Proceedings of the IEEE 24th International Conference on Tools with Artificial Intelligence, 2012

Prediction of antimicrobial activity of peptides using relational machine learning.

Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 2012

Extending the ball-histogram method with continuous distributions and an application to prediction of DNA-binding proteins.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012

2011

Block-wise construction of tree-like relational features with monotone reducibility and redundancy.

Ondrej Kuzelka, Filip Zelezný

Mach. Learn., 2011

Gaussian Logic for Predictive Classification.

Ondrej Kuzelka, Andrea Szabóová, Matej Holec, Filip Zelezný

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Prediction of DNA-Binding Propensity of Proteins by the Ball-Histogram Method.

Andrea Szabóová, Ondrej Kuzelka, Sergio Morales E., Filip Zelezný, Jakub Tolar

Proceedings of the Bioinformatics Research and Applications - 7th International Symposium, 2011

Gaussian logic and its applications in bioinformatics.

Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný

Proceedings of the ACM International Conference on Bioinformatics, 2011

2010

Taming the Complexity of Inductive Logic Programming.

Filip Zelezný, Ondrej Kuzelka

Proceedings of the SOFSEM 2010: Theory and Practice of Computer Science, 2010

Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples.

Ondrej Kuzelka, Filip Zelezný

Proceedings of the Inductive Logic Programming - 20th International Conference, 2010

Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming.

Roman Barták, Ondrej Kuzelka, Filip Zelezný

Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem.

Roman Barták, Ondrej Kuzelka, Filip Zelezný

Proceedings of the Abstraction, 2010

2009

Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties.

Ondrej Kuzelka, Filip Zelezný

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

A Restarted Strategy for Efficient Subsumption Testing.

Ondrej Kuzelka, Filip Zelezný

Fundam. Informaticae, 2008

Fast estimation of first-order clause coverage through randomization and maximum likelihood.

Ondrej Kuzelka, Filip Zelezný

Proceedings of the Machine Learning, 2008