Matthias Broecheler
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 10%
- Information Systems
- Computer Vision and Pattern Recognition
- Management Science and Operations Research
- Co-authors
- Lise GetoorStephen H. BachBert HuangAngelika KimmigV. S. SubrahmanianPaulo ShakarianDianne P. O’LearyCristian Molinaro
- Topics
- Bayesian Modeling and Causal Inference (3 papers)Data Management and Algorithms (3 papers)Complex Network Analysis Techniques (2 papers)
- Cited by
- Artificial IntelligenceStatistical and Nonlinear PhysicsManagement Science and Operations Research
- Journals
- ACM Transactions on Computational LogicLirias (KU Leuven)Neural Information Processing Systems
- Partner nations
- United StatesItalyBelgium
In The Last Decade
Matthias Broecheler
7 papers receiving 160 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 121
- Statistical and Nonlinear Physics 46
- Information Systems 29
- Computer Vision and Pattern Recognition 27
- Management Science and Operations Research 22
Countries citing papers authored by Matthias Broecheler
This map shows the geographic impact of Matthias Broecheler'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 Matthias Broecheler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Broecheler more than expected).
Fields of papers citing papers by Matthias Broecheler
This network shows the impact of papers produced by Matthias Broecheler. 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 Matthias Broecheler. The network helps show where Matthias Broecheler may publish in the future.
Co-authorship network of co-authors of Matthias Broecheler
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Broecheler. A scholar is included among the top collaborators of Matthias Broecheler 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 Matthias Broecheler. Matthias Broecheler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization | 24 |
| 3 | A short introduction to probabilistic soft logic | 95 |
| 4 | 1 | |
| 5 | Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning | 11 |
| 6 | 26 | |
| 7 | Promises kept, promises broken: an axiomatic and quantitative treatment of fulfillment | 4 |
About Matthias Broecheler
Matthias Broecheler is a scholar working on Signal Processing, Management Science and Operations Research and Computer Science Applications, having authored 7 papers that have together received 171 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Data Management and Algorithms (3 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (121 citations), Statistical and Nonlinear Physics (46 citations) and Management Science and Operations Research (22 citations). Matthias Broecheler has collaborated with scholars based in United States, Italy and Belgium. Frequent co-authors include Lise Getoor, Stephen H. Bach, Bert Huang, Angelika Kimmig, V. S. Subrahmanian, Paulo Shakarian, Dianne P. O’Leary, Cristian Molinaro, Sarit Kraus and Gerardo I. Simari. Their work appears in journals such as ACM Transactions on Computational Logic, Lirias (KU Leuven) and Neural Information Processing Systems.
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.