Wannes Meert - RankMe

129 papers A* 16A 8B 9C 2Misc 1Journal 55Unranked 37

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Correction: Steering the LoCoMotif: Using domain knowledge in time series motif discovery. Data Min. Knowl. Discov. Aras Yurtman, Daan Van Wesenbeeck, Wannes Meert, Hendrik Blockeel
2026	A*	`conf`	InTimeAD: Interactive Time Series Anomaly Detection. AAAI Louis Carpentier, Wannes Meert, Mathias Verbeke
2026	J	`jnl`	Quantitative evaluation of motif sets in time series. Data Min. Knowl. Discov. Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
2025	J	`jnl`	AIA: A Customized Multi-Core RISC-V SoC for Discrete Sampling Workloads in 16 nm. IEEE J. Solid State Circuits Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst
2025	A*	`conf`	Compressing tree ensembles through Level-wise Optimization and Pruning. ICML Laurens Devos, Timo Martens, Deniz Can Oruc, Wannes Meert, Hendrik Blockeel, Jesse Davis
2025	J	`jnl`	MC CoRR Shirui Zhao, Jun Yin, Lingyun Yao, Martin Andraud, Wannes Meert, Marian Verhelst
2025	—	`conf`	MotiPlus and MotiSet: Discovering the Best Set of Motiflets in Time Series. ECML/PKDD (7) Len Feremans, Patrick Schäfer, Wannes Meert
2025	A	`conf`	Neurosymbolic OCR for Handwritten Tax Forms. ECAI Quinten Dewulf, Robin Manhaeve, Wannes Meert, Luc De Raedt
2025	—	`conf`	Queryable and Interpretable PU Learning Through Probabilistic Circuits. ECML/PKDD (3) Sieben Bocklandt, Vincent Derkinderen, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers, Luc De Raedt, Wannes Meert
2025	J	`jnl`	Steering the LoCoMotif: Using Domain Knowledge in Time Series Motif Discovery. CoRR Aras Yurtman, Daan Van Wesenbeeck, Wannes Meert, Hendrik Blockeel
2025	J	`jnl`	Steering the LoCoMotif: Using domain knowledge in time series motif discovery. Data Min. Knowl. Discov. Aras Yurtman, Daan Van Wesenbeeck, Wannes Meert, Hendrik Blockeel
2025	J	`jnl`	Tailored Transformation Invariance for Industrial Anomaly Detection. CoRR Mariette Schönfeld, Wannes Meert, Hendrik Blockeel
2025	J	`jnl`	Warping and Matching Subsequences Between Time Series. CoRR Simiao Lin, Wannes Meert, Pieter Robberechts, Hendrik Blockeel
2025	J	`jnl`	dtaianomaly: A Python library for time series anomaly detection. CoRR Louis Carpentier, Nick Seeuws, Wannes Meert, Mathias Verbeke
2024	J	`jnl`	LoCoMotif: discovering time-warped motifs in time series. Data Min. Knowl. Discov. Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
2024	J	`jnl`	Machine learning with a reject option: a survey. Mach. Learn. Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2024	J	`jnl`	Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned. Mach. Learn. Jesse Davis, Lotte Bransen, Laurens Devos, Arne Jaspers, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy
2024	A	`conf`	Pattern-based Time Series Semantic Segmentation with Gradual State Transitions. SDM Louis Carpentier, Len Feremans, Wannes Meert, Mathias Verbeke
2024	J	`jnl`	Quantitative Evaluation of Motif Sets in Time Series. CoRR Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
2024	J	`jnl`	TSFuse: automated feature construction for multiple time series data. Mach. Learn. Arne De Brabandere, Tim Op De Beéck, Kilian Hendrickx, Wannes Meert, Jesse Davis
2024	J	`jnl`	Time-Shifted Transformers for Driver Identification Using Vehicle Data. IEEE Trans. Intell. Transp. Syst. Wim Govers, Aras Yurtman, Turgay Aslandere, Nicole Eikelenberg, Wannes Meert, Jesse Davis
2023	J	`jnl`	A Machine Learning Approach Towards SKILL Code Autocompletion. CoRR Enrique Dehaerne, Bappaditya Dey, Wannes Meert
2023	A	`conf`	A novel reject option applied to sleep stage scoring. SDM Dries Van der Plas, Wannes Meert, Johan Verbraecken, Jesse Davis
2023	J	`jnl`	AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. CoRR Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, Hendrik Blockeel
2023	J	`jnl`	Deriving Comprehensible Theories from Probabilistic Circuits. CoRR Sieben Bocklandt, Wannes Meert, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers
2023	—	`conf`	Detecting Evasion Attacks in Deployed Tree Ensembles. ECML/PKDD (5) Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
2023	—	`conf`	Estimating Dynamic Time Warping Distance Between Time Series with Missing Data. ECML/PKDD (5) Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel
2023	J	`jnl`	LoCoMotif: Discovering time-warped motifs in time series. CoRR Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
2022	J	`jnl`	Adversarial Example Detection in Deployed Tree Ensembles. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2022	—	`conf`	Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. BNAIC/BENELEARN Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers
2022	J	`jnl`	Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. CoRR Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers
2022	—	`conf`	Bitpaths: Compressing Datasets Without Decreasing Predictive Performance. PKDD/ECML Workshops (1) Loren Nuyts, Laurens Devos, Wannes Meert, Jesse Davis
2022	J	`jnl`	Code Generation Using Machine Learning: A Systematic Review. IEEE Access Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt, Wannes Meert
2022	A*	`conf`	DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. MICRO Nimish Shah, Wannes Meert, Marian Verhelst
2022	J	`jnl`	DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. CoRR Nimish Shah, Wannes Meert, Marian Verhelst
2022	J	`jnl`	DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. IEEE J. Solid State Circuits Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst
2022	A	`conf`	Discrete Samplers for Approximate Inference in Probabilistic Machine Learning. DATE Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst
2022	B	`conf`	Elastic Product Quantization for Time Series. DS Pieter Robberechts, Wannes Meert, Jesse Davis
2022	J	`jnl`	Elastic Product Quantization for Time Series. CoRR Pieter Robberechts, Wannes Meert, Jesse Davis
2022	—	`conf`	Evaluating Sports Analytics Models: Challenges, Approaches, and Lessons Learned. EBeM@IJCAI Jesse Davis, Lotte Bransen, Laurens Devos, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy
2022	J	`jnl`	GraphOpt: Constrained-Optimization-Based Parallelization of Irregular Graphs. IEEE Trans. Parallel Distributed Syst. Nimish Shah, Wannes Meert, Marian Verhelst
2022	—	`conf`	Multi-domain Active Learning for Semi-supervised Anomaly Detection. ECML/PKDD (4) Vincent Vercruyssen, Lorenzo Perini, Wannes Meert, Jesse Davis
2022	B	`conf`	Parameter Learning in ProbLog with Annotated Disjunctions. IDA Wen-Chi Yang, Arcchit Jain, Luc De Raedt, Wannes Meert
2021	—	`conf`	9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. ISSCC Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst
2021	J	`jnl`	Acceleration of probabilistic reasoning through custom processor architecture. CoRR Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
2021	A*	`conf`	An Automated Engineering Assistant: Learning Parsers for Technical Drawings. AAAI Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
2021	A*	`conf`	Automated Reasoning and Learning for Automated Payroll Management. AAAI Sebastijan Dumancic, Wannes Meert, Stijn Goethals, Tim Stuyckens, Jelle Huygen, Koen Denies
2021	J	`jnl`	DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm. CoRR Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst
2021	J	`jnl`	Evaluation of Automated Hypnogram Analysis on Multi-Scored Polysomnographies. Frontiers Digit. Health Dries Van der Plas, Johan Verbraecken, Marc Willemen, Wannes Meert, Jesse Davis
2021	J	`jnl`	GRAPHOPT: constrained optimization-based parallelization of irregular graphs. CoRR Nimish Shah, Wannes Meert, Marian Verhelst
2021	C	`conf`	Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. ADMA Kilian Hendrickx, Wannes Meert, Bram Cornelis, Jesse Davis
2021	J	`jnl`	Machine Learning with a Reject Option: A survey. CoRR Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
2021	J	`jnl`	ProbLP: A framework for low-precision probabilistic inference. CoRR Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
2021	A	`conf`	Verifying Tree Ensembles by Reasoning about Potential Instances. SDM Laurens Devos, Wannes Meert, Jesse Davis
2021	A*	`conf`	Versatile Verification of Tree Ensembles. ICML Laurens Devos, Wannes Meert, Jesse Davis
2020	A	`conf`	"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. SDM Vincent Vercruyssen, Wannes Meert, Jesse Davis
2020	A	`conf`	Acceleration of probabilistic reasoning through custom processor architecture. DATE Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
2020	J	`jnl`	Additive Tree Ensembles: Reasoning About Potential Instances. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2020	J	`jnl`	Crowdsourced Wireless Spectrum Anomaly Detection. IEEE Trans. Cogn. Commun. Netw. Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin
2020	B	`conf`	Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst
2020	—	`conf`	Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. IoT Streams/ITEM@PKDD/ECML Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst
2020	A*	`conf`	Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. AAAI Vincent Vercruyssen, Wannes Meert, Jesse Davis
2020	J	`jnl`	Versatile Verification of Tree Ensembles. CoRR Laurens Devos, Wannes Meert, Jesse Davis
2019	—	`conf`	A Framework for Pattern Mining and Anomaly Detection in Multi-dimensional Time Series and Event Logs. NFMCP@PKDD/ECML Len Feremans, Vincent Vercruyssen, Wannes Meert, Boris Cule, Bart Goethals
2019	—	`conf`	A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. BNAIC/BENELEARN Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs
2019	—	`conf`	A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. PKDD/ECML Workshops (2) Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs
2019	J	`jnl`	A general anomaly detection framework for fleet-based condition monitoring of machines. CoRR Kilian Hendrickx, Wannes Meert, Yves Mollet, Johan Gyselinck, Bram Cornelis, Konstantinos C. Gryllias, Jesse Davis
2019	J	`jnl`	An Automated Engineering Assistant: Learning Parsers for Technical Drawings. CoRR Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
2019	J	`jnl`	Crowdsourced wireless spectrum anomaly detection. CoRR Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin
2019	—	`conf`	Fast Gradient Boosting Decision Trees with Bit-Level Data Structures. ECML/PKDD (1) Laurens Devos, Wannes Meert, Jesse Davis
2019	—	`conf`	Learning Parsers for Technical Drawings. PKDD/ECML Workshops (1) Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
2019	A*	`conf`	Learning Relational Representations with Auto-encoding Logic Programs. IJCAI Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel
2019	J	`jnl`	Learning Relational Representations with Auto-encoding Logic Programs. CoRR Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel
2019	—	`conf`	On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. EMC2@NeurIPS Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst
2019	—	`conf`	Pattern-Based Anomaly Detection in Mixed-Type Time Series. ECML/PKDD (1) Len Feremans, Vincent Vercruyssen, Boris Cule, Wannes Meert, Bart Goethals
2019	A*	`conf`	ProbLP: A framework for low-precision probabilistic inference. DAC Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
2019	A*	`conf`	Towards Hardware-Aware Tractable Learning of Probabilistic Models. NeurIPS Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck
2019	J	`jnl`	Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features. IEEE Trans. Cogn. Commun. Netw. Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin
2018	J	`jnl`	COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series. CoRR Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
2018	B	`conf`	COBRASTS: A New Approach to Semi-supervised Clustering of Time Series. DS Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
2018	J	`jnl`	Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors. IEEE Trans. Cogn. Commun. Netw. Sreeraj Rajendran, Wannes Meert, Domenico Giustiniano, Vincent Lenders, Sofie Pollin
2018	J	`jnl`	Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification. IEEE J. Emerg. Sel. Topics Circuits Syst. Laura Isabel Galindez Olascoaga, Komail M. H. Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
2018	A*	`conf`	Fatigue Prediction in Outdoor Runners Via Machine Learning and Sensor Fusion. KDD Tim Op De Beéck, Wannes Meert, Kurt Schütte, Benedicte Vanwanseele, Jesse Davis
2018	B	`conf`	Feature noise tuning for resource efficient Bayesian Network Classifiers. ESANN Laura Isabel Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
2018	—	`conf`	Interactive Time Series Clustering with COBRASTS. ECML/PKDD (3) Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
2018	—	`conf`	Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver. DMLE/IOTSTREAMING@PKDD/ECML Pieter Robberechts, Maarten Bosteels, Jesse Davis, Wannes Meert
2018	—	`conf`	SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features. DySPAN Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin
2018	A*	`conf`	Semi-Supervised Anomaly Detection with an Application to Water Analytics. ICDM Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Baumer, Jesse Davis
2018	—	`conf`	Towards Resource-Efficient Classifiers for Always-On Monitoring. ECML/PKDD (3) Jonas Vlasselaer, Wannes Meert, Marian Verhelst
2017	J	`jnl`	Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors. CoRR Sreeraj Rajendran, Wannes Meert, Domenico Giustiniano, Vincent Lenders, Sofie Pollin
2017	—	`conf`	Power and spreading factor control in low power wide area networks. ICC Brecht Reynders, Wannes Meert, Sofie Pollin
2017	—	`conf`	Transfer Learning for Time Series Anomaly Detection. IAL@PKDD/ECML Vincent Vercruyssen, Wannes Meert, Jesse Davis
2016	J	`jnl`	A 90 nm CMOS, 6µW Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection. IEEE J. Solid State Circuits Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst
2016	—	`conf`	Energy consumption profiling using Gaussian processes. IEEE Conf. on Intelligent Systems Christiaan Leysen, Mathias Verbeke, Pierre Dagnely, Wannes Meert
2016	J	`jnl`	Exploiting local and repeated structure in Dynamic Bayesian Networks. Artif. Intell. Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
2016	Misc	`conf`	Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends. ACSSC Laura Isabel Galindez Olascoaga, Komail M. H. Badami, V. Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst
2016	—	`conf`	Extending Naive Bayes with Precision-tunable Feature Variables for Resource-efficient Sensor Fusion. AI-IoT@ECAI Laura Isabel Galindez Olascoaga, Wannes Meert, Herman Bruyninckx, Marian Verhelst
2016	—	`conf`	Knowledge Compilation and Weighted Model Counting for Inference in Probabilistic Logic Programs. AAAI Workshop: Beyond NP Jonas Vlasselaer, Angelika Kimmig, Anton Dries, Wannes Meert, Luc De Raedt
2016	J	`jnl`	Lifted generative learning of Markov logic networks. Mach. Learn. Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis
2016	—	`conf`	Range and coexistence analysis of long range unlicensed communication. ICT Brecht Reynders, Wannes Meert, Sofie Pollin
2016	J	`jnl`	T Int. J. Approx. Reason. Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
2016	J	`jnl`	Theory reconstruction: a representation learning view on predicate invention. CoRR Sebastijan Dumancic, Wannes Meert, Hendrik Blockeel
2015	—	`conf`	24.2 Context-aware hierarchical information-sensing in a 6μW 90nm CMOS voice activity detector. ISSCC Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst
2015	A*	`conf`	Anytime Inference in Probabilistic Logic Programs with Tp-Compilation. IJCAI Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
2015	J	`jnl`	LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines. Eng. Appl. Artif. Intell. Rocco Langone, Carlos Alzate, Bart De Ketelaere, Jonas Vlasselaer, Wannes Meert, Johan A. K. Suykens
2015	J	`jnl`	Optimal resource usage in ultra-low-power sensor interfaces through context- and resource-cost-aware machine learning. Neurocomputing Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst
2015	—	`conf`	ProbLog2: Probabilistic Logic Programming. ECML/PKDD (3) Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer, Luc De Raedt
2014	A	`conf`	Condition Monitoring with Incomplete Observations. ECAI Jonas Vlasselaer, Wannes Meert, Rocco Langone, Luc De Raedt
2014	B	`conf`	Context- and cost-aware feature selection in ultra-low-power sensor interfaces. ESANN Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst
2014	—	`conf`	Efficient Probabilistic Inference for Dynamic Relational Models. StarAI@AAAI Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
2014	—	`conf`	Inhibited Effects in CP-Logic. Probabilistic Graphical Models Wannes Meert, Joost Vennekens
2014	A*	`conf`	Skolemization for Weighted First-Order Model Counting. KR Guy Van den Broeck, Wannes Meert, Adnan Darwiche
2014	B	`conf`	The Most Probable Explanation for Probabilistic Logic Programs with Annotated Disjunctions. ILP Dimitar Sht. Shterionov, Joris Renkens, Jonas Vlasselaer, Angelika Kimmig, Wannes Meert, Gerda Janssens
2014	—	`conf`	Ultra-low-power voice-activity-detector through context- and resource-cost-aware feature selection in decision trees. MLSP Steven Lauwereins, Wannes Meert, Jort F. Gemmeke, Marian Verhelst
2013	A*	`conf`	Bitsquatting: exploiting bit-flips for fun, or profit? WWW Nick Nikiforakis, Steven Van Acker, Wannes Meert, Lieven Desmet, Frank Piessens, Wouter Joosen
2013	—	`conf`	Lifted Generative Parameter Learning. StarAI@AAAI Guy Van den Broeck, Wannes Meert, Jesse Davis
2013	C	`conf`	Rule-based Hand Posture Recognition using Qualitative Finger Configurations Acquired with the Kinect. ICPRAM Lieven Billiet, José Oramas M., McElory Hoffmann, Wannes Meert, Laura Antanas
2013	J	`jnl`	Skolemization for Weighted First-Order Model Counting. CoRR Guy Van den Broeck, Wannes Meert, Adnan Darwiche
2011	—	`—`	Inference and Learning for Directed Probabilistic Logic Models (Inferentie en leren voor gerichte probabilistische logische modellen). Wannes Meert
2011	A*	`conf`	Lifted Probabilistic Inference by First-Order Knowledge Compilation. IJCAI Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt
2011	—	`conf`	SessionShield: Lightweight Protection against Session Hijacking. ESSoS Nick Nikiforakis, Wannes Meert, Yves Younan, Martin Johns, Wouter Joosen
2010	J	`jnl`	CHR(PRISM)-based Probabilistic Logic Learning CoRR Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
2010	J	`jnl`	CHR(PRISM)-based probabilistic logic learning. Theory Pract. Log. Program. Jon Sneyers, Wannes Meert, Joost Vennekens, Yoshitaka Kameya, Taisuke Sato
2010	—	`conf`	First-Order Bayes-Ball. ECML/PKDD (2) Wannes Meert, Nima Taghipour, Hendrik Blockeel
2009	—	`conf`	An Exercise with Statistical Relational Learning Systems. MLG/SRL@ILP Maurice Bruynooghe, Daan Fierens, Bernd Gutmann, Angelika Kimmig, Niels Landwehr, Wannes Meert, Ingo Thon, Luc De Raedt
2009	B	`conf`	CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods. ILP Wannes Meert, Jan Struyf, Hendrik Blockeel
2009	—	`conf`	First-Order Bayes-Ball for CP-Logic. MLG/SRL@ILP Nima Taghipour, Wannes Meert, Jan Struyf, Hendrik Blockeel
2008	J	`jnl`	Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques. Fundam. Informaticae Wannes Meert, Jan Struyf, Hendrik Blockeel
2006	B	`conf`	Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks. ILP Hendrik Blockeel, Wannes Meert