Wannes Meert

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 92

Top Venues

Katholieke Universiteit Leuven, Belgium (PHD)

Education History

Katholieke Universiteit Leuven, Belgium

PHD

Publications

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) (2024)
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) (2024)
Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
Machine learning with a reject option: a survey. Mach. Learn. 113 (5) (2024)
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) (2024)
Louis Carpentier, Len Feremans, Wannes Meert, Mathias Verbeke
Pattern-based Time Series Semantic Segmentation with Gradual State Transitions. SDM (2024)
Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
LoCoMotif: discovering time-warped motifs in time series. Data Min. Knowl. Discov. 38 (4) (2024)
Sieben Bocklandt, Wannes Meert, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers
Deriving Comprehensible Theories from Probabilistic Circuits. CoRR (2023)
Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, Hendrik Blockeel
AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. CoRR (2023)
Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel
Estimating Dynamic Time Warping Distance Between Time Series with Missing Data. ECML/PKDD (5) (2023)
Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel
LoCoMotif: Discovering time-warped motifs in time series. CoRR (2023)
Laurens Devos, Lorenzo Perini, Wannes Meert, Jesse Davis
Detecting Evasion Attacks in Deployed Tree Ensembles. ECML/PKDD (5) (2023)
Enrique Dehaerne, Bappaditya Dey, Wannes Meert
A Machine Learning Approach Towards SKILL Code Autocompletion. CoRR (2023)
Dries Van der Pias, Wannes Meert, Johan Verbraecken, Jesse Davis
A novel reject option applied to sleep stage scoring. SDM (2023)
Nimish Shah, Wannes Meert, Marian Verhelst
GraphOpt: Constrained-Optimization-Based Parallelization of Irregular Graphs. IEEE Trans. Parallel Distributed Syst. 33 (12) (2022)
Wen-Chi Yang, Arcchit Jain, Luc De Raedt, Wannes Meert
Parameter Learning in ProbLog with Annotated Disjunctions. IDA (2022)
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 (2022)
Vincent Vercruyssen, Lorenzo Perini, Wannes Meert, Jesse Davis
Multi-domain Active Learning for Semi-supervised Anomaly Detection. ECML/PKDD (4) (2022)
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)
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) (2022)
Laurens Devos, Wannes Meert, Jesse Davis
Adversarial Example Detection in Deployed Tree Ensembles. CoRR (2022)
Nimish Shah, Wannes Meert, Marian Verhelst
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. MICRO (2022)
Nimish Shah, Wannes Meert, Marian Verhelst
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. CoRR (2022)
Loren Nuyts, Laurens Devos, Wannes Meert, Jesse Davis
Bitpaths: Compressing Datasets Without Decreasing Predictive Performance. PKDD/ECML Workshops (1) (2022)
Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst
Discrete Samplers for Approximate Inference in Probabilistic Machine Learning. DATE (2022)
Enrique Dehaerne, Bappaditya Dey, Sandip Halder, Stefan De Gendt, Wannes Meert
Code Generation Using Machine Learning: A Systematic Review. IEEE Access 10 (2022)
Pieter Robberechts, Wannes Meert, Jesse Davis
Elastic Product Quantization for Time Series. CoRR (2022)
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)
Pieter Robberechts, Wannes Meert, Jesse Davis
Elastic Product Quantization for Time Series. DS (2022)
Laurens Devos, Wannes Meert, Jesse Davis
Versatile Verification of Tree Ensembles. ICML (2021)
Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis
Machine Learning with a Reject Option: A survey. CoRR (2021)
Nimish Shah, Wannes Meert, Marian Verhelst
GRAPHOPT: constrained optimization-based parallelization of irregular graphs. CoRR (2021)
Laurens Devos, Wannes Meert, Jesse Davis
Verifying Tree Ensembles by Reasoning about Potential Instances. SDM (2021)
Sebastijan Dumancic, Wannes Meert, Stijn Goethals, Tim Stuyckens, Jelle Huygen, Koen Denies
Automated Reasoning and Learning for Automated Payroll Management. AAAI (2021)
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 (2021)
Kilian Hendrickx, Wannes Meert, Bram Cornelis, Jesse Davis
Know Your Limits: Machine Learning with Rejection for Vehicle Engineering. ADMA (2021)
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 (2021)
Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
ProbLP: A framework for low-precision probabilistic inference. CoRR (2021)
Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
An Automated Engineering Assistant: Learning Parsers for Technical Drawings. AAAI (2021)
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)
Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
Acceleration of probabilistic reasoning through custom processor architecture. CoRR (2021)
Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin
Crowdsourced Wireless Spectrum Anomaly Detection. IEEE Trans. Cogn. Commun. Netw. 6 (2) (2020)
Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA (2020)
Laurens Devos, Wannes Meert, Jesse Davis
Additive Tree Ensembles: Reasoning About Potential Instances. CoRR (2020)
Vincent Vercruyssen, Wannes Meert, Jesse Davis
"Now you see it, now you don't!" Detecting Suspicious Pattern Absences in Continuous Time Series. SDM (2020)
Vincent Vercruyssen, Wannes Meert, Jesse Davis
Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection. AAAI (2020)
Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
Acceleration of probabilistic reasoning through custom processor architecture. DATE (2020)
Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. IoT Streams/ITEM@PKDD/ECML (2020)
Laurens Devos, Wannes Meert, Jesse Davis
Versatile Verification of Tree Ensembles. CoRR (2020)
Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel
Learning Relational Representations with Auto-encoding Logic Programs. CoRR (2019)
Len Feremans, Vincent Vercruyssen, Boris Cule, Wannes Meert, Bart Goethals
Pattern-Based Anomaly Detection in Mixed-Type Time Series. ECML/PKDD (1) (2019)
Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
ProbLP: A framework for low-precision probabilistic inference. DAC (2019)
Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck
Towards Hardware-Aware Tractable Learning of Probabilistic Models. NeurIPS (2019)
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)
Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel
Learning Relational Representations with Auto-encoding Logic Programs. IJCAI (2019)
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)
Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin
Unsupervised Wireless Spectrum Anomaly Detection With Interpretable Features. IEEE Trans. Cogn. Commun. Netw. 5 (3) (2019)
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 (2019)
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)
Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
Learning Parsers for Technical Drawings. PKDD/ECML Workshops (1) (2019)
Laurens Devos, Wannes Meert, Jesse Davis
Fast Gradient Boosting Decision Trees with Bit-Level Data Structures. ECML/PKDD (1) (2019)
Sreeraj Rajendran, Vincent Lenders, Wannes Meert, Sofie Pollin
Crowdsourced wireless spectrum anomaly detection. CoRR (2019)
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)
Dries Van Daele, Nicholas Decleyre, Herman Dubois, Wannes Meert
An Automated Engineering Assistant: Learning Parsers for Technical Drawings. CoRR (2019)
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)
Sreeraj Rajendran, Wannes Meert, Vincent Lenders, Sofie Pollin
SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features. DySPAN (2018)
Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
Interactive Time Series Clustering with COBRASTS. ECML/PKDD (3) (2018)
Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series. CoRR (2018)
Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Baumer, Jesse Davis
Semi-Supervised Anomaly Detection with an Application to Water Analytics. ICDM (2018)
Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
COBRASTS: A New Approach to Semi-supervised Clustering of Time Series. DS (2018)
Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Towards Resource-Efficient Classifiers for Always-On Monitoring. ECML/PKDD (3) (2018)
Laura Isabel Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Feature noise tuning for resource efficient Bayesian Network Classifiers. ESANN (2018)
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) (2018)
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)
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) (2018)
Vincent Vercruyssen, Wannes Meert, Jesse Davis
Transfer Learning for Time Series Anomaly Detection. IAL@PKDD/ECML (2017)
Sreeraj Rajendran, Wannes Meert, Domenico Giustiniano, Vincent Lenders, Sofie Pollin
Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors. CoRR (2017)
Brecht Reynders, Wannes Meert, Sofie Pollin
Power and spreading factor control in low power wide area networks. ICC (2017)
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)
Christiaan Leysen, Mathias Verbeke, Pierre Dagnely, Wannes Meert
Energy consumption profiling using Gaussian processes. IEEE Conf. on Intelligent Systems (2016)
Sebastijan Dumancic, Wannes Meert, Hendrik Blockeel
Theory reconstruction: a representation learning view on predicate invention. CoRR (2016)
Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
-Compilation for inference in probabilistic logic programs. Int. J. Approx. Reason. 78 (2016)
Brecht Reynders, Wannes Meert, Sofie Pollin
Range and coexistence analysis of long range unlicensed communication. ICT (2016)
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) (2016)
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)
Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
Exploiting local and repeated structure in Dynamic Bayesian Networks. Artif. Intell. 232 (2016)
Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis
Lifted generative learning of Markov logic networks. Mach. Learn. 103 (1) (2016)
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)
Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt
Anytime Inference in Probabilistic Logic Programs with Tp-Compilation. IJCAI (2015)
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)
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 (2015)
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)
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 (2015)
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)
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)
Guy Van den Broeck, Wannes Meert, Adnan Darwiche
Skolemization for Weighted First-Order Model Counting. KR (2014)
Jonas Vlasselaer, Wannes Meert, Rocco Langone, Luc De Raedt
Condition Monitoring with Incomplete Observations. ECAI (2014)
Wannes Meert, Joost Vennekens
Inhibited Effects in CP-Logic. Probabilistic Graphical Models (2014)
Jonas Vlasselaer, Wannes Meert, Guy Van den Broeck, Luc De Raedt
Efficient Probabilistic Inference for Dynamic Relational Models. AAAI Workshop: Statistical Relational Artificial Intelligence (2014)
Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst
Context- and cost-aware feature selection in ultra-low-power sensor interfaces. ESANN (2014)
Nick Nikiforakis, Steven Van Acker, Wannes Meert, Lieven Desmet, Frank Piessens, Wouter Joosen
Bitsquatting: exploiting bit-flips for fun, or profit? WWW (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Wannes Meert