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Researcher
Wannes Meert
- Disciplines:Artificial intelligence
Affiliations
- Declarative Languages and Artificial Intelligence (DTAI) (Division)
Member
From1 Aug 2020 → Today - Informatics Section (Division)
Member
From1 Sep 2006 → 4 Aug 2020
Projects
1 - 10 of 22
- SPECTRAI - Spectral image Processing with Efficiently Compressed TensoRs and AIFrom1 Oct 2023 → TodayFunding: IOF - technology concept exploration
- Low rank tensor approximation techniques for up- and downdating of online time series clusteringFrom25 Sep 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Low rank tensor approximation techniques for up- and downdating of massive online time series clusteringFrom1 Jan 2023 → TodayFunding: FWO research project (including WEAVE projects)
- Advanced methods for analysis of structurally complex dataFrom1 Oct 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Counting shades of data quality: uncovering the notions of AI data quality, personal data quality and personal data accuracyFrom1 Sep 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Context Aware Anomaly Detection in Dynamic Industrial SettingsFrom1 Sep 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Automating Data WranglingFrom1 Jan 2022 → 31 Dec 2023Funding: IOF - technology validation in lab
- Anomaly Detection in Massive Time SeriesFrom1 Jan 2021 → 31 Dec 2022Funding: IWT / VLAIO personal funding - innovation mandates
- Contextual Anomaly Detection for Complex Industrial AssetsFrom1 Jan 2021 → 30 Jun 2023Funding: VLAIO ICON Artificial Intelligence (AI-ICON)
- AI in Industry: Learning and Reasoning for AutomationFrom1 Jan 2021 → TodayFunding: IOF - mandates
Publications
41 - 50 of 115
- Power Efficient Analog and Mixed-Signal Architectures for Sensing Systems(2019)
Authors: Komail Badami, Marian Verhelst, Wannes Meert
- A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes(2019)
Authors: Mathias Verbeke, Wannes Meert
Pages: 1 - 3 - ProbLP: A framework for low-precision probabilistic inference(2019)
Authors: Nimish Shirishbhai Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst
Pages: 190:1 - 6 - A Framework for Pattern Mining and Anomaly Detection in Multi-Dimensional Time Series and Event Logs(2019)
Authors: Vincent Vercruyssen, Wannes Meert
Pages: 3 - 20Number of pages: 17 - On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications(2019)
Authors: Wannes Meert, Nimish Shirishbhai Shah, Marian Verhelst
Pages: 66 - 70Number of pages: 5 - Learning Relational Representations with Auto-encoding Logic Programs(2019)
Authors: Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel
Pages: 6081 - 6087 - Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification(2018)
Authors: Laura Isabel Galindez Olascoaga, Komail Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Pages: 858 - 872 - Cross-Layer Self-Adaptivity for Ultra-Low Power Responsive IoT Devices: Analysing Task Hierarchy and Task Adaptivity at Different Optimisation Levels(2018)
Authors: Steven Lauwereins, Marian Verhelst, Wannes Meert
- COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series(2018)
Authors: Toon Van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel
Pages: 179 - 193 - Towards resource-efficient classifiers for always-on monitoring(2018)
Authors: Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Pages: 305 - 321
Linked dataset
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