Tijl De Bie
- Molecular Biology top 5%
- Artificial Intelligence top 2%
- Plant Science top 5%
- Genetics top 5%
- Computer Vision and Pattern Recognition top 2%
- Co-authors
- Nello CristianiniMatthew W. HahnJeffery P. DemuthJason StajichWilliam Stafford NobleMichael I. JordanGert LanckrietChi-Ngon Nguyen
- Topics
- Data Mining Algorithms and Applications (22 papers)Data Management and Algorithms (17 papers)Complex Network Analysis Techniques (16 papers)
- Partner nations
- BelgiumUnited KingdomUnited States
In The Last Decade
Tijl De Bie
111 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 174
- Molecular Biology 1.6k
- Artificial Intelligence 691
- Plant Science 618
- Genetics 541
- Computer Vision and Pattern Recognition 436
Countries citing papers authored by Tijl De Bie
This map shows the geographic impact of Tijl De Bie'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 Tijl De Bie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tijl De Bie more than expected).
Fields of papers citing papers by Tijl De Bie
This network shows the impact of papers produced by Tijl De Bie. 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 Tijl De Bie. The network helps show where Tijl De Bie may publish in the future.
Co-authorship network of co-authors of Tijl De Bie
This figure shows the co-authorship network connecting the top 25 collaborators of Tijl De Bie. A scholar is included among the top collaborators of Tijl De Bie 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 Tijl De Bie. Tijl De Bie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | Quantifying and reducing imbalance in networks | 2 |
| 5 | Scalable Dyadic Independence Models with Local and Global Constraints | 1 |
| 6 | Adapted NMFD update procedure for removing double hits in drum mixture decompositions | 1 |
| 7 | Mining Topological Structure in Graphs through Forest Representations | 3 |
| 8 | The boundary coefficient : a vertex measure for visualizing and finding structure in weighted graphs | 1 |
| 9 | Conditional Network Embeddings. | 2 |
| 10 | The normalized Friedkin-Johnsen model (a work-in-progress report) | 0 |
| 11 | Formalising the subjective interestingness of a linear projection of a data set : two examples | 0 |
| 12 | Machine learning and knowledge discovery in databases: ECML-PKDD Proceedings, Part II | 0 |
| 13 | 0 | |
| 14 | Flu Detector - Tracking Epidemics on Twitter | 1 |
| 15 | Magic Moments for Structured Output Prediction | 4 |
| 16 | A metamorphosis of Canonical Correlation Analysis into Multivariate Maximum Margin Learning | 11 |
| 17 | Deploying SDP for machine learning | 2 |
| 18 | 33 | |
| 19 | A Framework for Genomic Data Fusion and its Application to Membrane Protein Prediction | 4 |
| 20 | Convex Methods for Transduction | 79 |
About Tijl De Bie
Tijl De Bie is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 124 papers that have together received 3.6k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (22 papers), Data Management and Algorithms (17 papers) and Complex Network Analysis Techniques (16 papers). The work is most often cited by research in Signal Processing (348 citations), Molecular Biology (1.6k citations) and Artificial Intelligence (691 citations). Tijl De Bie has collaborated with scholars based in Belgium, United Kingdom and United States. Frequent co-authors include Nello Cristianini, Matthew W. Hahn, Jeffery P. Demuth, Jason Stajich, William Stafford Noble, Michael I. Jordan, Gert Lanckriet, Chi-Ngon Nguyen, Raúl Santos‐Rodríguez and Matt McVicar. Their work appears in journals such as Bioinformatics, PLoS ONE and Communications of the ACM.
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.