Mark Chavira
Impact in
- Artificial Intelligence top 5%
- Bayesian Modeling and Causal Inference
- Logic, Reasoning, and Knowledge
- Machine Learning and Algorithms
- AI-based Problem Solving and Planning
- Software top 10%
Papers in
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- Bayesian Modeling and Causal Inference 9
- AI-based Problem Solving and Planning 3
- Logic, Reasoning, and Knowledge 3
- Bayesian Methods and Mixture Models 1
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- Data Management and Algorithms 3
- Co-authors
- Adnan Y. Darwiche (10 shared papers)Manfred Jaeger (2 shared papers)Scott D. Poll (3 shared papers)Ole Jakob Mengshoel (3 shared papers)Serdar Uckun (3 shared papers)Jinbo Huang (1 shared paper)David L. Allen (1 shared paper)Knot Pipatsrisawat (1 shared paper)
- Journals
- Artificial Intelligence (1 paper)International Journal of Approximate Reasoning (1 paper)IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans (1 paper)Lecture notes in computer science (1 paper)Uncertainty in Artificial Intelligence (1 paper)
- Partner nations
- United StatesAustraliaDenmark
In The Last Decade
Mark Chavira
11 papers receiving 500 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 455
- Software 52
- Signal Processing 80
- Computational Mathematics 4
- Computational Theory and Mathematics 105
Countries citing papers authored by Mark Chavira
This map shows the geographic impact of Mark Chavira'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 Chavira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Chavira more than expected).
Fields of papers citing papers by Mark Chavira
This network shows the impact of papers produced by Mark Chavira. 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 Chavira. The network helps show where Mark Chavira may publish in the future.
Co-authors
The 9 scholars most cited alongside Mark Chavira, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 226 | |
| 2 | 2010 | 77 | |
| 3 | 2005 | 76 | |
| 4 | Compiling Bayesian Networks with Local Structure | 2008 | 69 |
| 5 | Solving MAP Exactly by Searching on Compiled Arithmetic Circuits | 2006 | 26 |
| 6 | 2008 | 21 | |
| 7 | 2018 | 12 | |
| 8 | Exploiting evidence in probabilistic inference | 2005 | 11 |
| 9 | 2006 | 10 | |
| 10 | Compiling Relational Bayesian Networks for Exact Inference | 2004 | 7 |
| 11 | Efficient Probabilistic Diagnostics for Electrical Power Systems | 2008 | 1 |
About Mark Chavira
Mark Chavira is a scholar working on Artificial Intelligence, Signal Processing, Software, Statistics and Probability and Philosophy, having authored 11 papers that have together received 536 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (9 papers), AI-based Problem Solving and Planning (3 papers), Logic, Reasoning, and Knowledge (3 papers), Data Management and Algorithms (3 papers), Software Testing and Debugging Techniques (2 papers), Bayesian Methods and Mixture Models (1 paper), Hermeneutics and Narrative Identity (1 paper) and Formal Methods in Verification (1 paper). The work is most often cited by research in Artificial Intelligence (455 citations), Software (52 citations), Signal Processing (80 citations), Computational Mathematics (4 citations) and Computational Theory and Mathematics (105 citations). Mark Chavira has collaborated with scholars based in United States, Australia and Denmark. Frequent co-authors include Adnan Y. Darwiche, Manfred Jaeger, Scott D. Poll, Ole Jakob Mengshoel, Serdar Uckun, Jinbo Huang, David L. Allen, Knot Pipatsrisawat and Arthur Choi. Their work appears in journals such as Artificial Intelligence, International Journal of Approximate Reasoning, IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans, Lecture notes in computer science 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.