Pedro Domingos
About
In The Last Decade
Pedro Domingos
182 papers receiving 21.5k citations
Hit Papers
Peers
Comparison fields: 5 of 215
- Artificial Intelligence 14.5k
- Information Systems 5.4k
- Computer Networks and Communications 3.7k
- Statistical and Nonlinear Physics 3.0k
- Signal Processing 2.8k
Countries citing papers authored by Pedro Domingos
This map shows the geographic impact of Pedro Domingos'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 Pedro Domingos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Domingos more than expected).
Fields of papers citing papers by Pedro Domingos
This network shows the impact of papers produced by Pedro Domingos. 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 Pedro Domingos. The network helps show where Pedro Domingos may publish in the future.
Co-authorship network of co-authors of Pedro Domingos
This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Domingos. A scholar is included among the top collaborators of Pedro Domingos 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 Pedro Domingos. Pedro Domingos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 13 | |
| 3 | Deep Symmetry Networks | 76 |
| 4 | Learning Markov Logic Networks Using Structural Motifs | 58 |
| 5 | Approximate Inference by Compilation to Arithmetic Circuits | 5 |
| 6 | Exploiting logical structure in lifted probabilistic inference | 11 |
| 7 | Machine reading: a Killer app for statistical relational AI | 12 |
| 8 | Learning Efficient Markov Networks | 19 |
| 9 | A general method for reducing the complexity of relational inference and its application to MCMC | 48 |
| 10 | Sound and efficient inference with probabilistic and deterministic dependencies | 155 |
| 11 | Memory-efficient inference in relational domains | 51 |
| 12 | Collective object identification | 3 |
| 13 | Dynamic probabilistic relational models | 46 |
| 14 | Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining | 341 |
| 15 | Adaptive web navigation for wireless devices | 66 |
| 16 | A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering | 109 |
| 17 | Version Space Algebra and its Application to Programming by Demonstration | 63 |
| 18 | Process-oriented estimation of generalization error | 6 |
| 19 | 9 | |
| 20 | The RISE 2.0 System: A Case Study in Multistrategy Learning | 7 |
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.