default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDWannes Meert
◁ ▶ joint publications with coauthor community group 1
- > Home > Persons > Wannes Meert
Publications
- 2024
[j21]Daan Van Wesenbeeck
, Aras Yurtman, Wannes Meert, Hendrik Blockeel:
LoCoMotif: discovering time-warped motifs in time series. Data Min. Knowl. Discov. 38(4): 2276-2305 (2024)- [j20]Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis:
Machine learning with a reject option: a survey. Mach. Learn. 113(5): 3073-3110 (2024) - [j19]Arne De Brabandere, Tim Op De Beéck, Kilian Hendrickx, Wannes Meert, Jesse Davis:
TSFuse: automated feature construction for multiple time series data. Mach. Learn. 113(8): 5001-5056 (2024) - [j18]Jesse Davis, Lotte Bransen, Laurens Devos, Arne Jaspers, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy:
Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned. Mach. Learn. 113(9): 6977-7010 (2024) - [j17]Wim Govers, Aras Yurtman, Turgay Aslandere, Nicole Eikelenberg, Wannes Meert, Jesse Davis:
Time-Shifted Transformers for Driver Identification Using Vehicle Data. IEEE Trans. Intell. Transp. Syst. 25(5): 3767-3776 (2024) - [c66]Louis Carpentier, Len Feremans, Wannes Meert, Mathias Verbeke:
Pattern-based Time Series Semantic Segmentation with Gradual State Transitions. SDM 2024: 316-324 - 2023
- [c65]Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis:
Detecting Evasion Attacks in Deployed Tree Ensembles. ECML/PKDD (5) 2023: 120-136 - [c64]Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel:
Estimating Dynamic Time Warping Distance Between Time Series with Missing Data. ECML/PKDD (5) 2023: 221-237 - [c63]Dries Van der Pias, Wannes Meert, Johan Verbraecken, Jesse Davis:
A novel reject option applied to sleep stage scoring. SDM 2023: 820-828 - [i24]Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, Hendrik Blockeel:
AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. CoRR abs/2305.12958 (2023) - [i23]Sieben Bocklandt, Wannes Meert, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Deriving Comprehensible Theories from Probabilistic Circuits. CoRR abs/2311.13379 (2023) - [i22]Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel:
LoCoMotif: Discovering time-warped motifs in time series. CoRR abs/2311.17582 (2023) - 2022
- [j15]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. IEEE J. Solid State Circuits 57(8): 2586-2596 (2022) - [j14]Nimish Shah, Wannes Meert, Marian Verhelst:
GraphOpt: Constrained-Optimization-Based Parallelization of Irregular Graphs. IEEE Trans. Parallel Distributed Syst. 33(12): 3321-3332 (2022) - [c62]Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. BNAIC/BENELEARN 2022: 47-64 - [c61]Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst:
Discrete Samplers for Approximate Inference in Probabilistic Machine Learning. DATE 2022: 1221-1226 - [c60]Pieter Robberechts, Wannes Meert, Jesse Davis:
Elastic Product Quantization for Time Series. DS 2022: 157-172 - [c59]Wen-Chi Yang, Arcchit Jain, Luc De Raedt, Wannes Meert:
Parameter Learning in ProbLog with Annotated Disjunctions. IDA 2022: 378-391 - [c58]Jesse Davis, Lotte Bransen, Laurens Devos, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy:
Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned. EBeM@IJCAI 2022 - [c57]Nimish Shah, Wannes Meert, Marian Verhelst:
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. MICRO 2022: 1288-1307 - [c56]Loren Nuyts, Laurens Devos, Wannes Meert, Jesse Davis:
Bitpaths: Compressing Datasets Without Decreasing Predictive Performance. PKDD/ECML Workshops (1) 2022: 261-268 - [c55]Vincent Vercruyssen, Lorenzo Perini, Wannes Meert, Jesse Davis:
Multi-domain Active Learning for Semi-supervised Anomaly Detection. ECML/PKDD (4) 2022: 485-501 - [i20]Pieter Robberechts, Wannes Meert, Jesse Davis:
Elastic Product Quantization for Time Series. CoRR abs/2201.01856 (2022) - [i19]Laurens Devos, Wannes Meert, Jesse Davis:
Adversarial Example Detection in Deployed Tree Ensembles. CoRR abs/2206.13083 (2022) - [i18]Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. CoRR abs/2210.01515 (2022) - [i17]Nimish Shah, Wannes Meert, Marian Verhelst:
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. CoRR abs/2210.13184 (2022) - 2021
- [j13]Dries Van der Plas, Johan Verbraecken, Marc Willemen, Wannes Meert, Jesse Davis:
Evaluation of Automated Hypnogram Analysis on Multi-Scored Polysomnographies. Frontiers Digit. Health 3: 707589 (2021) - [c54]Sebastijan Dumancic, Wannes Meert, Stijn Goethals, Tim Stuyckens, Jelle Huygen, Koen Denies:
Automated Reasoning and Learning for Automated Payroll Management. AAAI 2021: 15107-15116 - [c53]Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert:
An Automated Engineering Assistant: Learning Parsers for Technical Drawings. AAAI 2021: 15195-15203 - [c52]Kilian Hendrickx, Wannes Meert, Bram Cornelis, Jesse Davis:
Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. ADMA 2021: 273-288 - [c51]Laurens Devos, Wannes Meert, Jesse Davis:
Versatile Verification of Tree Ensembles. ICML 2021: 2654-2664 - [c50]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. ISSCC 2021: 150-152 - [c49]Laurens Devos, Wannes Meert, Jesse Davis:
Verifying Tree Ensembles by Reasoning about Potential Instances. SDM 2021: 450-458 - [i16]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. CoRR abs/2103.00216 (2021) - [i15]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. CoRR abs/2103.00266 (2021) - [i14]Nimish Shah, Wannes Meert, Marian Verhelst:
GRAPHOPT: constrained optimization-based parallelization of irregular graphs. CoRR abs/2105.01976 (2021) - [i13]Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis:
Machine Learning with a Reject Option: A survey. CoRR abs/2107.11277 (2021) - [i12]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm. CoRR abs/2112.05660 (2021) - 2020
- [j12]Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin:
Crowdsourced Wireless Spectrum Anomaly Detection. IEEE Trans. Cogn. Commun. Netw. 6(2): 694-703 (2020) - [c48]Vincent Vercruyssen, Wannes Meert, Jesse Davis:
Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. AAAI 2020: 6054-6061 - [c47]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. DATE 2020: 322-325 - [c46]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA 2020: 184-196 - [c45]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst:
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. IoT Streams/ITEM@PKDD/ECML 2020: 283-295 - [c44]Vincent Vercruyssen, Wannes Meert, Jesse Davis:
"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. SDM 2020: 127-135 - [i11]Laurens Devos, Wannes Meert, Jesse Davis:
Additive Tree Ensembles: Reasoning About Potential Instances. CoRR abs/2001.11905 (2020) - [i10]Laurens Devos, Wannes Meert, Jesse Davis:
Versatile Verification of Tree Ensembles. CoRR abs/2010.13880 (2020) - 2019
- [j11]Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin:
Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features. IEEE Trans. Cogn. Commun. Netw. 5(3): 637-647 (2019) - [c43]Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs:
A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. BNAIC/BENELEARN 2019 - [c42]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. DAC 2019: 190 - [c41]Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel:
Learning Relational Representations with Auto-encoding Logic Programs. IJCAI 2019: 6081-6087 - [c40]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. EMC2@NeurIPS 2019: 66-70 - [c39]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck:
Towards Hardware-Aware Tractable Learning of Probabilistic Models. NeurIPS 2019: 13726-13736 - [c38]Len Feremans, Vincent Vercruyssen, Wannes Meert, Boris Cule, Bart Goethals:
A Framework for Pattern Mining and Anomaly Detection in Multi-dimensional Time Series and Event Logs. NFMCP@PKDD/ECML 2019: 3-20 - [c37]Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert:
Learning Parsers for Technical Drawings. PKDD/ECML Workshops (1) 2019: 51-56 - [c36]Len Feremans, Vincent Vercruyssen, Boris Cule, Wannes Meert, Bart Goethals:
Pattern-Based Anomaly Detection in Mixed-Type Time Series. ECML/PKDD (1) 2019: 240-256 - [c35]Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs:
A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. PKDD/ECML Workshops (2) 2019: 414-425 - [c34]Laurens Devos, Wannes Meert, Jesse Davis:
Fast Gradient Boosting Decision Trees with Bit-Level Data Structures. ECML/PKDD (1) 2019: 590-606 - [i9]Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin:
Crowdsourced wireless spectrum anomaly detection. CoRR abs/1903.05408 (2019) - [i8]Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel:
Learning Relational Representations with Auto-encoding Logic Programs. CoRR abs/1903.12577 (2019) - [i7]Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert:
An Automated Engineering Assistant: Learning Parsers for Technical Drawings. CoRR abs/1909.08552 (2019) - [i6]Kilian Hendrickx, Wannes Meert, Yves Mollet, Johan Gyselinck, Bram Cornelis, Konstantinos C. Gryllias, Jesse Davis:
A general anomaly detection framework for fleet-based condition monitoring of machines. CoRR abs/1912.12941 (2019) - 2018
- [j10]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 858-872 (2018) - [j9]Sreeraj Rajendran, Wannes Meert, Domenico Giustiniano, Vincent Lenders, Sofie Pollin:
Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors. IEEE Trans. Cogn. Commun. Netw. 4(3): 433-445 (2018) - [c33]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
COBRASTS: A New Approach to Semi-supervised Clustering of Time Series. DS 2018: 179-193 - [c32]Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin:
SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features. DySPAN 2018: 1-9 - [c31]Laura Isabel Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Feature noise tuning for resource efficient Bayesian Network Classifiers. ESANN 2018 - [c30]Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Baumer, Jesse Davis:
Semi-Supervised Anomaly Detection with an Application to Water Analytics. ICDM 2018: 527-536 - [c29]Tim Op De Beéck, Wannes Meert, Kurt Schütte, Benedicte Vanwanseele, Jesse Davis:
Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion. KDD 2018: 606-615 - [c28]Pieter Robberechts, Maarten Bosteels, Jesse Davis, Wannes Meert:
Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver. DMLE/IOTSTREAMING@PKDD/ECML 2018: 55-67 - [c27]Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Towards Resource-Efficient Classifiers for Always-On Monitoring. ECML/PKDD (3) 2018: 305-321 - [c26]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
Interactive Time Series Clustering with COBRASTS. ECML/PKDD (3) 2018: 654-657 - [i5]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series. CoRR abs/1805.00779 (2018) - 2017
- [c25]Brecht Reynders, Wannes Meert, Sofie Pollin:
Power and spreading factor control in low power wide area networks. ICC 2017: 1-6 - [c24]Vincent Vercruyssen, Wannes Meert, Jesse Davis:
Transfer Learning for Time Series Anomaly Detection. IAL@PKDD/ECML 2017: 27-36 - [i4]Sreeraj Rajendran, Wannes Meert, Domenico Giustiniano, Vincent Lenders, Sofie Pollin:
Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors. CoRR abs/1707.08908 (2017) - 2016
- [j8]Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt:
Exploiting local and repeated structure in Dynamic Bayesian Networks. Artif. Intell. 232: 43-53 (2016) - [j7]Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt:
TP-Compilation for inference in probabilistic logic programs. Int. J. Approx. Reason. 78: 15-32 (2016) - [j6]Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst:
A 90 nm CMOS, 6µW Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection. IEEE J. Solid State Circuits 51(1): 291-302 (2016) - [j5]Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis:
Lifted generative learning of Markov logic networks. Mach. Learn. 103(1): 27-55 (2016) - [c23]Jonas Vlasselaer, Angelika Kimmig, Anton Dries, Wannes Meert, Luc De Raedt:
Knowledge Compilation and Weighted Model Counting for Inference in Probabilistic Logic Programs. AAAI Workshop: Beyond NP 2016 - [c22]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, V. Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst:
Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends. ACSSC 2016: 1027-1031 - [c21]Laura Isabel Galindez Olascoaga, Wannes Meert, Herman Bruyninckx, Marian Verhelst:
Extending Naive Bayes with Precision-tunable Feature Variables for Resource-efficient Sensor Fusion. AI-IoT@ECAI 2016: 23-30 - [c20]Brecht Reynders, Wannes Meert, Sofie Pollin:
Range and coexistence analysis of long range unlicensed communication. ICT 2016: 1-6 - [c19]Christiaan Leysen, Mathias Verbeke, Pierre Dagnely, Wannes Meert:
Energy consumption profiling using Gaussian processes. IEEE Conf. on Intelligent Systems 2016: 470-477 - [i3]Sebastijan Dumancic, Wannes Meert, Hendrik Blockeel:
Theory reconstruction: a representation learning view on predicate invention. CoRR abs/1606.08660 (2016) - 2015
- [j4]Rocco Langone, Carlos Alzate, Bart De Ketelaere, Jonas Vlasselaer, Wannes Meert, Johan A. K. Suykens:
LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines. Eng. Appl. Artif. Intell. 37: 268-278 (2015) - [j3]Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst:
Optimal resource usage in ultra-low-power sensor interfaces through context- and resource-cost-aware machine learning. Neurocomputing 169: 236-245 (2015) - [c18]Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt:
Anytime Inference in Probabilistic Logic Programs with Tp-Compilation. IJCAI 2015: 1852-1858 - [c17]Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst:
24.2 Context-aware hierarchical information-sensing in a 6μW 90nm CMOS voice activity detector. ISSCC 2015: 1-3 - [c16]Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer, Luc De Raedt:
ProbLog2: Probabilistic Logic Programming. ECML/PKDD (3) 2015: 312-315 - 2014
- [c15]Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt:
Efficient Probabilistic Inference for Dynamic Relational Models. StarAI@AAAI 2014 - [c14]Jonas Vlasselaer, Wannes Meert, Rocco Langone, Luc De Raedt:
Condition Monitoring with Incomplete Observations. ECAI 2014: 1215-1216 - [c13]Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst:
Context- and cost-aware feature selection in ultra-low-power sensor interfaces. ESANN 2014 - [c12]Dimitar Sht. Shterionov, Joris Renkens, Jonas Vlasselaer, Angelika Kimmig, Wannes Meert, Gerda Janssens:
The Most Probable Explanation for Probabilistic Logic Programs with Annotated Disjunctions. ILP 2014: 139-153 - [c11]Guy Van den Broeck, Wannes Meert, Adnan Darwiche:
Skolemization for Weighted First-Order Model Counting. KR 2014 - [c10]Steven Lauwereins, Wannes Meert, Jort F. Gemmeke, Marian Verhelst:
Ultra-low-power voice-activity-detector through context- and resource-cost-aware feature selection in decision trees. MLSP 2014: 1-6 - [c9]Wannes Meert, Joost Vennekens:
Inhibited Effects in CP-Logic. Probabilistic Graphical Models 2014: 350-365 - 2013
- [c8]Guy Van den Broeck, Wannes Meert, Jesse Davis:
Lifted Generative Parameter Learning. StarAI@AAAI 2013 - [c7]Lieven Billiet, José Oramas M., McElory Hoffmann, Wannes Meert, Laura Antanas:
Rule-based Hand Posture Recognition using Qualitative Finger Configurations Acquired with the Kinect. ICPRAM 2013: 539-542 - [c6]Nick Nikiforakis, Steven Van Acker, Wannes Meert, Lieven Desmet, Frank Piessens, Wouter Joosen:
Bitsquatting: exploiting bit-flips for fun, or profit? WWW 2013: 989-998 - [i2]Guy Van den Broeck, Wannes Meert, Adnan Darwiche:
Skolemization for Weighted First-Order Model Counting. CoRR abs/1312.5378 (2013) - 2011
- [c5]Nick Nikiforakis, Wannes Meert, Yves Younan, Martin Johns, Wouter Joosen:
SessionShield: Lightweight Protection against Session Hijacking. ESSoS 2011: 87-100 - [c4]Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt:
Lifted Probabilistic Inference by First-Order Knowledge Compilation. IJCAI 2011: 2178-2185 - 2010
- [j2]Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato:
CHR(PRISM)-based probabilistic logic learning. Theory Pract. Log. Program. 10(4-6): 433-447 (2010) - [c3]Wannes Meert, Nima Taghipour, Hendrik Blockeel:
First-Order Bayes-Ball. ECML/PKDD (2) 2010: 369-384 - [i1]Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato:
CHR(PRISM)-based Probabilistic Logic Learning. CoRR abs/1007.3858 (2010) - 2009
- [c2]Wannes Meert, Jan Struyf, Hendrik Blockeel:
CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods. ILP 2009: 96-109 - 2008
- [j1]Wannes Meert, Jan Struyf, Hendrik Blockeel:
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques. Fundam. Informaticae 89(1): 131-160 (2008) - 2006
- [c1]Hendrik Blockeel, Wannes Meert:
Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks. ILP 2006: 94-108
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 2024-08-23 18:33 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:
