Kuzelka, Ondrej

32 publications

NeurIPS 2024 Faster Repeated Evasion Attacks in Tree Ensembles Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis

IJCAI 2023 Counting and Sampling Models in First-Order Logic Ondrej Kuzelka

JAIR 2023 First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt

AAAI 2023 Lifted Inference with Linear Order Axiom Jan Tóth, Ondrej Kuzelka

IJCAI 2023 On Discovering Interesting Combinatorial Integer Sequences Martin Svatos, Peter Jung, Jan Tóth, Yuyi Wang, Ondrej Kuzelka

AAAI 2022 Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka

AISTATS 2021 Context-Specific Likelihood Weighting Nitesh Kumar, Ondřej Kuželka

MLJ 2021 Beyond Graph Neural Networks with Lifted Relational Neural Networks Gustav Sourek, Filip Zelezný, Ondrej Kuzelka

IJCAI 2021 Fast Algorithms for Relational Marginal Polytopes Yuanhong Wang, Timothy van Bremen, Juhua Pu, Yuyi Wang, Ondrej Kuzelka

UAI 2021 Faster Lifting for Two-Variable Logic Using Cell Graphs Timothy Bremen, Ondřej Kuželka

ICLR 2021 Lossless Compression of Structured Convolutional Models via Lifting Gustav Sourek, Filip Zelezny, Ondrej Kuzelka

UAI 2021 Neural Markov Logic Networks Giuseppe Marra, Ondřej Kuželka

JAIR 2021 Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers Ondrej Kuzelka

IJCAI 2020 Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry Timothy van Bremen, Ondrej Kuzelka

UAI 2020 Complex Markov Logic Networks: Expressivity and Liftability Ondrej Kuzelka

AISTATS 2020 Domain-Liftability of Relational Marginal Polytopes Ondrej Kuzelka, Yuyi Wang

PGM 2020 Lifted Weight Learning of Markov Logic Networks (Revisited One More Time) Ondrej Kuzelka, Vyacheslav Kungurtsev, Yuyi Wang

ICLR 2020 Neural Markov Logic Networks Giuseppe Marra, Ondřej Kuželka

AISTATS 2019 Lifted Weight Learning of Markov Logic Networks Revisited Ondrej Kuzelka, Vyacheslav Kungurtsev

UAI 2019 Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption Ondřej Kuželka, Jesse Davis

JAIR 2018 Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka

UAI 2018 PAC-Reasoning in Relational Domains Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert

AAAI 2018 Relational Marginal Problems: Theory and Estimation Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert

ECML-PKDD 2018 VC-Dimension Based Generalization Bounds for Relational Learning Ondrej Kuzelka, Yuyi Wang, Steven Schockaert

IJCAI 2017 Induction of Interpretable Possibilistic Logic Theories from Relational Data Ondrej Kuzelka, Jesse Davis, Steven Schockaert

IJCAI 2016 Bounds for Learning from Evolutionary-Related Data in the Realizable Case Ondrej Kuzelka, Yuyi Wang, Jan Ramon

IJCAI 2016 Learning Possibilistic Logic Theories from Default Rules Ondrej Kuzelka, Jesse Davis, Steven Schockaert

UAI 2015 Encoding Markov Logic Networks in Possibilistic Logic Ondrej Kuzelka, Jesse Davis, Steven Schockaert

MLJ 2011 Block-Wise Construction of Tree-like Relational Features with Monotone Reducibility and Redundancy Ondrej Kuzelka, Filip Zelezný

ECML-PKDD 2011 Gaussian Logic for Predictive Classification Ondrej Kuzelka, Andrea Szabóová, Matej Holec, Filip Zelezný

ICML 2009 Block-Wise Construction of Acyclic Relational Features with Monotone Irreducibility and Relevancy Properties Ondrej Kuzelka, Filip Zelezný

ICML 2008 Fast Estimation of First-Order Clause Coverage Through Randomization and Maximum Likelihood Ondrej Kuzelka, Filip Zelezný