Wannes Meert

2.4k citations
70 papers · 1.3k indexed · h-index 19
Topics
Bayesian Modeling and Causal Inference (24 papers)Anomaly Detection Techniques and Applications (11 papers)Logic, Reasoning, and Knowledge (10 papers)

In The Last Decade

Wannes Meert

63 papers receiving 1.2k citations

Peers

Wannes Meert
Comparison fields: 5 of 98
  • Artificial Intelligence 533
  • Electrical and Electronic Engineering 456
  • Computer Networks and Communications 413
  • Biomedical Engineering 232
  • Signal Processing 190
Replace Luis Antonio Ribot García with:
Luis Antonio Ribot García United States
Maurizio Mongelli Italy
Ahmad Akbari Iran
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Chieh-Jan Mike Liang United States
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Pedro C. Diniz United States
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Citations per field
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Citations per year

Countries citing papers authored by Wannes Meert

Since Specialization
Citations

This map shows the geographic impact of Wannes Meert's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wannes Meert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wannes Meert more than expected).

Fields of papers citing papers by Wannes Meert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wannes Meert. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wannes Meert. The network helps show where Wannes Meert may publish in the future.

Co-authorship network of co-authors of Wannes Meert

This figure shows the co-authorship network connecting the top 25 collaborators of Wannes Meert. A scholar is included among the top collaborators of Wannes Meert based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wannes Meert. Wannes Meert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 19
2 7
3 1
4 31
5 2
6 3
7 21
8
Knowledge compilation and weighted model counting for inference in probabilistic logic programs
1
9 164
10 13
11
Anytime inference in probabilistic logic programs with TP-compilation
14
12 30
13
Efficient probabilistic inference for dynamic relational models
1
14
Tractable learning of liftable Markov logic networks
3
15
Lifted generative parameter learning
5
16
Lifted inference for probabilistic programming
2
17 87
18
Contextual variable elimination with overlapping contexts
0
19
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
21
20
Learning Ground CP-logic Theories by means of Bayesian Network Techniques
5

About Wannes Meert

Wannes Meert is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (24 papers), Anomaly Detection Techniques and Applications (11 papers) and Logic, Reasoning, and Knowledge (10 papers). The work is most often cited by research in Computer Networks and Communications (413 citations), Signal Processing (190 citations) and Artificial Intelligence (533 citations). Wannes Meert has collaborated with scholars based in Belgium, United States and South Africa. Frequent co-authors include Sofie Pollin, Brecht Reynders, Jesse Davis, Marian Verhelst, Guy Van den Broeck, Steven Lauwereins, Luc De Raedt, Vincent Lenders, Sreeraj Rajendran and Nima Taghipour. Their work appears in journals such as PLoS ONE, IEEE Access and IEEE Journal of Solid-State Circuits.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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