Mark A. Paskin
- Computer Networks and Communications top 2%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Aerospace Engineering top 5%
- Co-authors
- Carlos GuestrinPeter BodíkSamuel MaddenKevin P. MurphyStanislav FuniakRahul SukthankarPraveen SeshadriStuart Russell
- Topics
- Distributed Sensor Networks and Detection Algorithms (5 papers)Robotics and Sensor-Based Localization (5 papers)Bayesian Modeling and Causal Inference (4 papers)
- Cited by
- Computer Networks and CommunicationsComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- Neural Information Processing SystemsInformation Processing in Sensor NetworksUncertainty in Artificial Intelligence
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Mark A. Paskin
15 papers receiving 911 citations
Peers
Comparison fields: 5 of 72
- Computer Networks and Communications 484
- Artificial Intelligence 405
- Computer Vision and Pattern Recognition 277
- Electrical and Electronic Engineering 253
- Aerospace Engineering 218
Countries citing papers authored by Mark A. Paskin
This map shows the geographic impact of Mark A. Paskin'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 Mark A. Paskin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Paskin more than expected).
Fields of papers citing papers by Mark A. Paskin
This network shows the impact of papers produced by Mark A. Paskin. 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 Mark A. Paskin. The network helps show where Mark A. Paskin may publish in the future.
Co-authorship network of co-authors of Mark A. Paskin
This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Paskin. A scholar is included among the top collaborators of Mark A. Paskin 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 Mark A. Paskin. Mark A. Paskin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 88 | |
| 2 | 77 | |
| 3 | 92 | |
| 4 | 49 | |
| 5 | 56 | |
| 6 | Exploiting locality in probabilistic inference | 5 |
| 7 | 298 | |
| 8 | Sample Propagation | 8 |
| 9 | Thin junction tree filters for simultaneous localization and mapping | 147 |
| 10 | Junction tree algorithms for solving sparse linear systems | 11 |
| 11 | Thin Junction Tree Filtering for Simultaneous Localization and Mapping | 8 |
| 12 | Linear-time inference in Hierarchical HMMs | 112 |
| 13 | Cubic-time Parsing and Learning Algorithms for Grammatical Bigram | 6 |
| 14 | Maximum-Entropy Probabilistic Logics | 11 |
| 15 | 21 |
About Mark A. Paskin
Mark A. Paskin is a scholar working on Artificial Intelligence, Computer Networks and Communications and Aerospace Engineering, having authored 15 papers that have together received 989 indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (5 papers), Robotics and Sensor-Based Localization (5 papers) and Bayesian Modeling and Causal Inference (4 papers). The work is most often cited by research in Computer Networks and Communications (484 citations), Computer Vision and Pattern Recognition (277 citations) and Artificial Intelligence (405 citations). Mark A. Paskin has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Carlos Guestrin, Peter Bodík, Samuel Madden, Kevin P. Murphy, Stanislav Funiak, Rahul Sukthankar, Praveen Seshadri and Stuart Russell. Their work appears in journals such as Neural Information Processing Systems, Information Processing in Sensor Networks and Uncertainty in Artificial Intelligence.
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.