This map shows the geographic impact of Avi Pfeffer'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 Avi Pfeffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Avi Pfeffer more than expected).
This network shows the impact of papers produced by Avi Pfeffer. 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 Avi Pfeffer. The network helps show where Avi Pfeffer may publish in the future.
Co-authorship network of co-authors of Avi Pfeffer
This figure shows the co-authorship network connecting the top 25 collaborators of Avi Pfeffer.
A scholar is included among the top collaborators of Avi Pfeffer 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 Avi Pfeffer. Avi Pfeffer is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Pfeffer, Avi, et al.. (2018). Structured Factored Inference for Probabilistic Programming.. International Conference on Artificial Intelligence and Statistics. 1224–1232.1 indexed citations
2.
Pfeffer, Avi, et al.. (2015). Reasoning on resident space object hierarchies using probabilistic programming. International Conference on Information Fusion. 1315–1321.3 indexed citations
3.
Pfeffer, Avi, et al.. (2013). Towards an Artificial Space Object Taxonomy. Advanced Maui Optical and Space Surveillance Technologies Conference.7 indexed citations
Pfeffer, Avi, et al.. (2009). Using reasoning patterns to help humans solve complex games. International Joint Conference on Artificial Intelligence. 33–39.2 indexed citations
7.
Pfeffer, Avi. (2009). CTPPL: a continuous time probabilistic programming language. International Joint Conference on Artificial Intelligence. 1943–1950.6 indexed citations
8.
Pfeffer, Avi, et al.. (2008). Using reasoning patterns to simplify games. National Conference on Artificial Intelligence. 1770–1771.1 indexed citations
Frogner, Charlie & Avi Pfeffer. (2007). Discovering Weakly-Interacting Factors in a Complex Stochastic Process. Neural Information Processing Systems. 20. 481–488.3 indexed citations
13.
Pfeffer, Avi & Kobi Gal. (2007). On the reasoning patterns of agents in games. National Conference on Artificial Intelligence. 102–109.6 indexed citations
14.
Pfeffer, Avi. (2007). Sampling with memoization. National Conference on Artificial Intelligence. 1263–1270.3 indexed citations
15.
Gal, Kobi & Avi Pfeffer. (2007). Modeling reciprocal behavior in human bilateral negotiation. National Conference on Artificial Intelligence. 815–820.36 indexed citations
16.
Pfeffer, Avi, et al.. (2004). A Hierarchical Approach to Onset Detection. The Journal of the Abraham Lincoln Association. 2004.13 indexed citations
17.
Gal, Kobi, et al.. (2004). Learning social preferences in games. Digital Access to Scholarship at Harvard (DASH) (Harvard University). 226–231.42 indexed citations
18.
Friedman, Nir, Daphne Koller, & Avi Pfeffer. (1998). Structured representation of complex stochastic systems. National Conference on Artificial Intelligence. 157–164.18 indexed citations
19.
Pfeffer, Avi, et al.. (1997). Learning probabilities for noisy first-order rules. International Joint Conference on Artificial Intelligence. 1316–1321.35 indexed citations
20.
Koller, Daphne & Avi Pfeffer. (1995). Generating and solving imperfect information games. International Joint Conference on Artificial Intelligence. 1185–1192.22 indexed citations
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.