default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDOndrej Kuzelka
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j15]Yuanhong Wang
, Juhua Pu, Yuyi Wang, Ondrej Kuzelka:
Lifted algorithms for symmetric weighted first-order model sampling. Artif. Intell. 331: 104114 (2024)- [j14]Peter Jung, Giuseppe Marra, Ondrej Kuzelka:
Quantified neural Markov logic networks. Int. J. Approx. Reason. 171: 109172 (2024) - [c56]Ondrej Kuzelka:
Model Counting and Sampling in First-Order Logic (Abstract of Invited Talk). Description Logics 2024 - [i29]Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis:
Faster Repeated Evasion Attacks in Tree Ensembles. CoRR abs/2402.08586 (2024) - [i28]Jan Tóth, Ondrej Kuzelka:
Complexity of Weighted First-Order Model Counting in the Two-Variable Fragment with Counting Quantifiers: A Bound to Beat. CoRR abs/2404.12905 (2024) - [i27]Qipeng Kuang, Ondrej Kuzelka, Yuanhong Wang, Yuyi Wang:
Bridging Weighted First Order Model Counting and Graph Polynomials. CoRR abs/2407.11877 (2024) - 2023
- [j13]Timothy van Bremen, Ondrej Kuzelka:
Lifted inference with tree axioms. Artif. Intell. 324: 103997 (2023) - [j12]Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt:
First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. J. Artif. Intell. Res. 77: 683-735 (2023) - [c55]Jan Tóth, Ondrej Kuzelka:
Lifted Inference with Linear Order Axiom. AAAI 2023: 12295-12304 - [c54]Martin Svatos, Peter Jung, Jan Tóth, Yuyi Wang, Ondrej Kuzelka:
On Discovering Interesting Combinatorial Integer Sequences. IJCAI 2023: 3338-3346 - [c53]Ondrej Kuzelka:
Counting and Sampling Models in First-Order Logic. IJCAI 2023: 7020-7025 - [c52]Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka:
On Exact Sampling in the Two-Variable Fragment of First-Order Logic. LICS 2023: 1-13 - [p1]Gustav Sír, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks: From Graphs to Deep Relational Learning. Compendium of Neurosymbolic Artificial Intelligence 2023: 308-336 - [i26]Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka:
On Exact Sampling in the Two-Variable Fragment of First-Order Logic. CoRR abs/2302.02730 (2023) - [i25]Martin Svatos, Peter Jung, Jan Tóth, Yuyi Wang, Ondrej Kuzelka:
On Discovering Interesting Combinatorial Integer Sequences. CoRR abs/2302.04606 (2023) - [i24]Yuanhong Wang, Juhua Pu, Yuyi Wang, Ondrej Kuzelka:
Lifted Algorithms for Symmetric Weighted First-Order Model Sampling. CoRR abs/2308.08828 (2023) - 2022
- [j11]Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt:
Learning Distributional Programs for Relational Autocompletion. Theory Pract. Log. Program. 22(1): 81-114 (2022) - [c51]Yuanhong Wang, Timothy van Bremen, Yuyi Wang, Ondrej Kuzelka:
Domain-Lifted Sampling for Universal Two-Variable Logic and Extensions. AAAI 2022: 10070-10079 - [i23]Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt:
First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs. CoRR abs/2201.11165 (2022) - [i22]Jan Tóth, Ondrej Kuzelka:
Lifted Inference with Linear Order Axiom. CoRR abs/2211.01164 (2022) - 2021
- [j10]Ondrej Kuzelka:
Weighted First-Order Model Counting in the Two-Variable Fragment With Counting Quantifiers. J. Artif. Intell. Res. 70: 1281-1307 (2021) - [j9]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond graph neural networks with lifted relational neural networks. Mach. Learn. 110(7): 1695-1738 (2021) - [c50]Nitesh Kumar, Ondrej Kuzelka:
Context-Specific Likelihood Weighting. AISTATS 2021: 2125-2133 - [c49]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Lossless Compression of Structured Convolutional Models via Lifting. ICLR 2021 - [c48]Yuanhong Wang, Timothy van Bremen, Juhua Pu, Yuyi Wang, Ondrej Kuzelka:
Fast Algorithms for Relational Marginal Polytopes. IJCAI 2021: 4266-4274 - [c47]Jáchym Barvínek, Timothy van Bremen, Yuyi Wang, Filip Zelezný, Ondrej Kuzelka:
Automatic Conjecturing of P-Recursions Using Lifted Inference. ILP 2021: 17-25 - [c46]Timothy van Bremen, Ondrej Kuzelka:
Lifted Inference with Tree Axioms. KR 2021: 599-608 - [c45]Giuseppe Marra, Ondrej Kuzelka:
Neural markov logic networks. UAI 2021: 908-917 - [c44]Timothy van Bremen, Ondrej Kuzelka:
Faster lifting for two-variable logic using cell graphs. UAI 2021: 1393-1402 - [i21]Nitesh Kumar, Ondrej Kuzelka:
Context-Specific Likelihood Weighting. CoRR abs/2101.09791 (2021) - 2020
- [c43]Ondrej Kuzelka, Yuyi Wang:
Domain-Liftability of Relational Marginal Polytopes. AISTATS 2020: 2284-2292 - [c42]Martin Svatos, Steven Schockaert, Jesse Davis, Ondrej Kuzelka:
STRiKE: Rule-Driven Relational Learning Using Stratified k-Entailment. ECAI 2020: 1515-1522 - [c41]Timothy van Bremen, Ondrej Kuzelka:
Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry. IJCAI 2020: 4252-4258 - [c40]Ondrej Kuzelka, Vyacheslav Kungurtsev, Yuyi Wang:
Lifted Weight Learning of Markov Logic Networks (Revisited One More Time). PGM 2020: 269-280 - [c39]Ondrej Kuzelka:
Complex Markov Logic Networks: Expressivity and Liftability. UAI 2020: 729-738 - [i20]Ondrej Kuzelka, Yuyi Wang:
Domain-Liftability of Relational Marginal Polytopes. CoRR abs/2001.05198 (2020) - [i19]Timothy van Bremen, Ondrej Kuzelka:
Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry. CoRR abs/2001.05263 (2020) - [i18]Nitesh Kumar, Ondrej Kuzelka, Luc De Raedt:
Learning Distributional Programs for Relational Autocompletion. CoRR abs/2001.08603 (2020) - [i17]Ondrej Kuzelka:
Markov Logic Networks with Complex Weights: Expressivity, Liftability and Fourier Transforms. CoRR abs/2002.10259 (2020) - [i16]Ondrej Kuzelka:
Lifted Inference in 2-Variable Markov Logic Networks with Function and Cardinality Constraints Using Discrete Fourier Transform. CoRR abs/2006.03432 (2020) - [i15]Ondrej Kuzelka:
Weighted First-Order Model Counting in the Two-Variable Fragment With Counting Quantifiers. CoRR abs/2007.05619 (2020) - [i14]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Beyond Graph Neural Networks with Lifted Relational Neural Networks. CoRR abs/2007.06286 (2020) - [i13]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Learning with Molecules beyond Graph Neural Networks. CoRR abs/2011.03488 (2020)
2010 – 2019
- 2019
- [c38]Ondrej Kuzelka, Vyacheslav Kungurtsev:
Lifted Weight Learning of Markov Logic Networks Revisited. AISTATS 2019: 1753-1761 - [c37]Arcchit Jain, Tal Friedman, Ondrej Kuzelka, Guy Van den Broeck, Luc De Raedt:
Scalable Rule Learning in Probabilistic Knowledge Bases. AKBC 2019 - [c36]Gustav Sourek, Filip Zelezný, Ondrej Kuzelka:
Scaling up relational templated neural models. NeSy@IJCAI 2019 - [c35]Ondrej Kuzelka, Jesse Davis:
Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption. UAI 2019: 1138-1148 - [i12]Ondrej Kuzelka, Vyacheslav Kungurtsev:
Lifted Weight Learning of Markov Logic Networks Revisited. CoRR abs/1903.03099 (2019) - [i11]Giuseppe Marra, Ondrej Kuzelka:
Neural Markov Logic Networks. CoRR abs/1905.13462 (2019) - 2018
- [j8]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures. J. Artif. Intell. Res. 62: 69-100 (2018) - [c34]Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert:
Relational Marginal Problems: Theory and Estimation. AAAI 2018: 6384-6391 - [c33]Thomas Ager, Ondrej Kuzelka, Steven Schockaert:
Modelling Salient Features as Directions in Fine-Tuned Semantic Spaces. CoNLL 2018: 530-540 - [c32]Víctor Gutiérrez-Basulto, Jean Christoph Jung, Ondrej Kuzelka:
Quantified Markov Logic Networks. KR 2018: 602-612 - [c31]Ondrej Kuzelka, Yuyi Wang, Steven Schockaert:
VC-Dimension Based Generalization Bounds for Relational Learning. ECML/PKDD (2) 2018: 259-275 - [c30]Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert:
PAC-Reasoning in Relational Domains. UAI 2018: 927-936 - [i10]Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert:
PAC-Reasoning in Relational Domains. CoRR abs/1803.05768 (2018) - [i9]Ondrej Kuzelka, Yuyi Wang, Steven Schockaert:
VC-Dimension Based Generalization Bounds for Relational Learning. CoRR abs/1804.06188 (2018) - [i8]Víctor Gutiérrez-Basulto, Jean Christoph Jung, Ondrej Kuzelka:
Markov Logic Networks with Statistical Quantifiers. CoRR abs/1807.01183 (2018) - 2017
- [c29]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Induction of Interpretable Possibilistic Logic Theories from Relational Data. IJCAI 2017: 1153-1159 - [c28]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. ILP 2017: 140-151 - [c27]Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Pruning Hypothesis Spaces Using Learned Domain Theories. ILP 2017: 152-168 - [i7]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Induction of Interpretable Possibilistic Logic Theories from Relational Data. CoRR abs/1705.07095 (2017) - [i6]Ondrej Kuzelka, Yuyi Wang, Jesse Davis, Steven Schockaert:
Relational Marginal Problems: Theory and Estimation. CoRR abs/1709.05825 (2017) - [i5]Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. CoRR abs/1710.02221 (2017) - 2016
- [j7]Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný:
Polynomial and Extensible Solutions in Lock-Chart Solving. Appl. Artif. Intell. 30(10): 923-941 (2016) - [c26]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Interpretable Encoding of Densities Using Possibilistic Logic. ECAI 2016: 1239-1247 - [c25]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Learning Possibilistic Logic Theories from Default Rules. IJCAI 2016: 1167-1173 - [c24]Ondrej Kuzelka, Yuyi Wang, Jan Ramon:
Bounds for Learning from Evolutionary-Related Data in the Realizable Case. IJCAI 2016: 1655-1661 - [c23]Gustav Sourek, Suresh Manandhar, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Learning Predictive Categories Using Lifted Relational Neural Networks. ILP 2016: 108-119 - [c22]Thomas Ager, Ondrej Kuzelka, Steven Schockaert:
Inducing Symbolic Rules from Entity Embeddings using Auto-encoders. NeSy@HLAI 2016 - [i4]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Learning Possibilistic Logic Theories from Default Rules. CoRR abs/1604.05273 (2016) - [i3]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract). CoRR abs/1611.06174 (2016) - 2015
- [j6]Matej Holec, Ondrej Kuzelka, Filip Zelezný:
Novel gene sets improve set-level classification of prokaryotic gene expression data. BMC Bioinform. 16: 348:1-348:8 (2015) - [c21]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Learning to Detect Network Intrusion from a Few Labeled Events and Background Traffic. AIMS 2015: 73-86 - [c20]Ondrej Kuzelka, Jan Ramon:
A Note on Restricted Forms of LGG. ILP (Late Breaking Papers) 2015: 62-68 - [c19]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Constructing Markov Logic Networks from First-Order Default Rules. ILP 2015: 91-105 - [c18]Ondrej Kuzelka, Jan Ramon:
Mine 'Em All: A Note on Mining All Graphs. ILP 2015: 106-121 - [c17]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoCo@NIPS 2015 - [c16]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Encoding Markov logic networks in Possibilistic Logic. UAI 2015: 454-463 - [i2]Ondrej Kuzelka, Jesse Davis, Steven Schockaert:
Encoding Markov Logic Networks in Possibilistic Logic. CoRR abs/1506.01432 (2015) - [i1]Gustav Sourek, Vojtech Aschenbrenner, Filip Zelezný, Ondrej Kuzelka:
Lifted Relational Neural Networks. CoRR abs/1508.05128 (2015) - 2014
- [j5]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
A method for reduction of examples in relational learning. J. Intell. Inf. Syst. 42(2): 255-281 (2014) - 2013
- [j4]Roman Barták, Radomír Cernoch, Ondrej Kuzelka, Filip Zelezný:
Formulating the template ILP consistency problem as a constraint satisfaction problem. Constraints An Int. J. 18(2): 144-165 (2013) - [c15]Gustav Sourek, Ondrej Kuzelka, Filip Zelezný:
Predicting Top-k Trends on Twitter using Graphlets and Time Features. ILP (Late Breaking Papers) 2013: 52-57 - 2012
- [j3]Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný, Jakub Tolar:
Prediction of DNA-binding propensity of proteins by the ball-histogram method using automatic template search. BMC Bioinform. 13(S-10): S3 (2012) - [c14]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Extending the ball-histogram method with continuous distributions and an application to prediction of DNA-binding proteins. BIBM 2012: 1-4 - [c13]Andrea Szabóová, Ondrej Kuzelka, Filip Zelezný:
Prediction of antimicrobial activity of peptides using relational machine learning. BIBM Workshops 2012: 575-580 - [c12]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Relational Learning with Polynomials. ICTAI 2012: 1145-1150 - [c11]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Bounded Least General Generalization. ILP 2012: 116-129 - [c10]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses. NFMCP 2012: 17-32 - 2011
- [j2]Ondrej Kuzelka, Filip Zelezný:
Block-wise construction of tree-like relational features with monotone reducibility and redundancy. Mach. Learn. 83(2): 163-192 (2011) - [c9]Ondrej Kuzelka, Andrea Szabóová, Filip Zelezný:
Gaussian logic and its applications in bioinformatics. BCB 2011: 496-498 - [c8]Andrea Szabóová, Ondrej Kuzelka, Sergio Morales E., Filip Zelezný, Jakub Tolar:
Prediction of DNA-Binding Propensity of Proteins by the Ball-Histogram Method. ISBRA 2011: 358-367 - [c7]Ondrej Kuzelka, Andrea Szabóová, Matej Holec, Filip Zelezný:
Gaussian Logic for Predictive Classification. ECML/PKDD (2) 2011: 277-292 - 2010
- [c6]Roman Barták, Ondrej Kuzelka, Filip Zelezný:
Formulating Template Consistency in Inductive Logic Programming as a Constraint Satisfaction Problem. Abstraction, Reformulation, and Approximation 2010 - [c5]Roman Barták, Ondrej Kuzelka, Filip Zelezný:
Using Constraint Satisfaction for Learning Hypotheses in Inductive Logic Programming. FLAIRS 2010 - [c4]Ondrej Kuzelka, Filip Zelezný:
Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. ILP 2010: 138-145 - [c3]Filip Zelezný, Ondrej Kuzelka:
Taming the Complexity of Inductive Logic Programming. SOFSEM 2010: 132-140
2000 – 2009
- 2009
- [c2]Ondrej Kuzelka, Filip Zelezný:
Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties. ICML 2009: 569-576 - 2008
- [j1]Ondrej Kuzelka, Filip Zelezný:
A Restarted Strategy for Efficient Subsumption Testing. Fundam. Informaticae 89(1): 95-109 (2008) - [c1]Ondrej Kuzelka, Filip Zelezný:
Fast estimation of first-order clause coverage through randomization and maximum likelihood. ICML 2008: 504-511
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-25 20:09 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
