Nima Taghipour
- Artificial Intelligence top 10%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Computer Networks and Communications
- Signal Processing
- Co-authors
- Ahmad A. KardanJesse DavisGuy Van den BroeckWannes MeertLuc De RaedtSaeed Shiry GhidaryHendrik BlockeelDaan Fierens
- Topics
- Bayesian Modeling and Causal Inference (8 papers)Machine Learning and Algorithms (4 papers)Recommender Systems and Techniques (4 papers)
- Journals
- Advanced MaterialsarXiv (Cornell University)Lirias (KU Leuven)
In The Last Decade
Nima Taghipour
12 papers receiving 229 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 182
- Information Systems 98
- Management Science and Operations Research 53
- Computer Networks and Communications 42
- Signal Processing 28
Countries citing papers authored by Nima Taghipour
This map shows the geographic impact of Nima Taghipour'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 Nima Taghipour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nima Taghipour more than expected).
Fields of papers citing papers by Nima Taghipour
This network shows the impact of papers produced by Nima Taghipour. 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 Nima Taghipour. The network helps show where Nima Taghipour may publish in the future.
Co-authorship network of co-authors of Nima Taghipour
This figure shows the co-authorship network connecting the top 25 collaborators of Nima Taghipour. A scholar is included among the top collaborators of Nima Taghipour 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 Nima Taghipour. Nima Taghipour is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 7 | |
| 3 | Lifted Probabilistic Inference by Variable Elimination | 1 |
| 4 | Completeness Results for Lifted Variable Elimination | 11 |
| 5 | 1 | |
| 6 | Lifted variable elimination with arbitrary constraints | 15 |
| 7 | Lifted inference for probabilistic programming | 2 |
| 8 | Generalized counting for lifted variable elimination | 6 |
| 9 | Recent advances in lifted inference at Leuven | 2 |
| 10 | 87 | |
| 11 | Biclustering of gene expression data using probabilistic logic learning | 1 |
| 12 | First-Order Bayes-Ball for CP-Logic | 5 |
| 13 | Utilizing Content to Enhance a Usage-Based Method for Web Recommendation based on Q-Learning | 1 |
| 14 | 3 | |
| 15 | 55 | |
| 16 | Enhancing a Web Recommender System based on Q Learning. | 1 |
| 17 | 54 |
About Nima Taghipour
Nima Taghipour is a scholar working on Computer Science Applications, Artificial Intelligence and Information Systems, having authored 17 papers that have together received 260 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (8 papers), Machine Learning and Algorithms (4 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (182 citations), Information Systems (98 citations) and Management Science and Operations Research (53 citations). Nima Taghipour has collaborated with scholars based in Belgium, Iran and Spain. Frequent co-authors include Ahmad A. Kardan, Jesse Davis, Guy Van den Broeck, Wannes Meert, Luc De Raedt, Saeed Shiry Ghidary, Hendrik Blockeel, Daan Fierens, Gerasimos Konstantatos and Carmelita Rodà. Their work appears in journals such as Advanced Materials, arXiv (Cornell University) and Lirias (KU Leuven).
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.