Joris M. Mooij
- Artificial Intelligence top 1%
- Molecular Biology top 10%
- Genetics top 2%
- Statistics and Probability top 1%
- Signal Processing top 5%
- Co-authors
- Tom HeskesChristiaan de LeeuwDaniëlle PosthumaDominik JanzingBernhard SchölkopfJonas PetersHilbert J. KappenPatrik O. Hoyer
- Topics
- Bayesian Modeling and Causal Inference (37 papers)Machine Learning and Algorithms (9 papers)Error Correcting Code Techniques (8 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaIEEE Transactions on Information Theory
- Partner nations
- NetherlandsGermanySwitzerland
In The Last Decade
Joris M. Mooij
43 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 172
- Artificial Intelligence 1.3k
- Molecular Biology 933
- Genetics 933
- Statistics and Probability 284
- Signal Processing 204
Countries citing papers authored by Joris M. Mooij
This map shows the geographic impact of Joris M. Mooij'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 Joris M. Mooij with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joris M. Mooij more than expected).
Fields of papers citing papers by Joris M. Mooij
This network shows the impact of papers produced by Joris M. Mooij. 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 Joris M. Mooij. The network helps show where Joris M. Mooij may publish in the future.
Co-authorship network of co-authors of Joris M. Mooij
This figure shows the co-authorship network connecting the top 25 collaborators of Joris M. Mooij. A scholar is included among the top collaborators of Joris M. Mooij 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 Joris M. Mooij. Joris M. Mooij is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Constraint-Based Causal Discovery In The Presence Of Cycles | 1 |
| 2 | Joint Causal Inference from Multiple Contexts | 28 |
| 3 | Constraint-Based Causal Discovery with Partial Ancestral Graphs in the presence of Cycles | 1 |
| 4 | Causal Transfer Learning. | 3 |
| 5 | 72 | |
| 6 | Theoretical Aspects of Cyclic Structural Causal Models | 2 |
| 7 | 105 | |
| 8 | Supplement - Learning Sparse Causal Models is not NP-hard | 0 |
| 9 | On causal and anticausal learning | 104 |
| 10 | 137 | |
| 11 | On Causal Discovery with Cyclic Additive Noise Models | 33 |
| 12 | Efficient inference in matrix-variate Gaussian models with iid observation noise | 37 |
| 13 | Probabilistic latent variable models for distinguishing between cause and effect | 44 |
| 14 | 160 | |
| 15 | Distinguishing between cause and effect | 18 |
| 16 | 8 | |
| 17 | Loop corrected belief propagation. | 11 |
| 18 | 11 | |
| 19 | Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks | 9 |
| 20 | 7 |
About Joris M. Mooij
Joris M. Mooij is a scholar working on Artificial Intelligence, Statistics and Probability and Signal Processing, having authored 47 papers that have together received 3.4k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (37 papers), Machine Learning and Algorithms (9 papers) and Error Correcting Code Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Statistics and Probability (284 citations) and Genetics (933 citations). Joris M. Mooij has collaborated with scholars based in Netherlands, Germany and Switzerland. Frequent co-authors include Tom Heskes, Christiaan de Leeuw, Daniëlle Posthuma, Dominik Janzing, Bernhard Schölkopf, Jonas Peters, Hilbert J. Kappen, Patrik O. Hoyer, Jakob Zscheischler and Kun Zhang. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.
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.