Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A model for reasoning about persistence and causation
Countries citing papers authored by Keiji Kanazawa
Since
Specialization
Citations
This map shows the geographic impact of Keiji Kanazawa'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 Keiji Kanazawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keiji Kanazawa more than expected).
This network shows the impact of papers produced by Keiji Kanazawa. 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 Keiji Kanazawa. The network helps show where Keiji Kanazawa may publish in the future.
Co-authorship network of co-authors of Keiji Kanazawa
This figure shows the co-authorship network connecting the top 25 collaborators of Keiji Kanazawa.
A scholar is included among the top collaborators of Keiji Kanazawa 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 Keiji Kanazawa. Keiji Kanazawa is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Russell, Stuart, et al.. (1995). Local learning in probabilistic networks with hidden variables. International Joint Conference on Artificial Intelligence. 1146–1152.89 indexed citations
5.
Huang, T.S., et al.. (1995). The BATmobile: towards a Bayesian automated taxi. International Joint Conference on Artificial Intelligence. 1878–1885.120 indexed citations
6.
Kanazawa, Keiji. (1994). Sensible decisions: toward a theory of decision-theoretic information invariants. National Conference on Artificial Intelligence. 77 ( Pt 1). 973–978.1 indexed citations
7.
Kanazawa, Keiji, et al.. (1994). A Decision-Theoretic Abductive Basis for Planning*.8 indexed citations
8.
Kanazawa, Keiji. (1992). Reasoning about time and probability.14 indexed citations
9.
Kanazawa, Keiji. (1991). A logic and time nets for probabilistic inference. National Conference on Artificial Intelligence. 360–365.27 indexed citations
10.
Kanazawa, Keiji & Thomas Dean. (1989). A model for projection and action. International Joint Conference on Artificial Intelligence. 985–990.35 indexed citations
11.
Boddy, Mark, Robert P. Goldman, Keiji Kanazawa, & Lynn Andrea Stein. (1989). Investigations of Model-Preference Defaults.1 indexed citations
12.
Dean, Thomas & Keiji Kanazawa. (1989). A model for reasoning about persistence and causation. Computational Intelligence. 5(2). 142–150.620 indexed citations breakdown →
13.
Dean, Taraneh & Keiji Kanazawa. (1989). Persistence and probabilistic projection. IEEE Transactions on Systems Man and Cybernetics. 19(3). 574–585.13 indexed citations
14.
Dean, Thomas & Keiji Kanazawa. (1988). Probabilistic temporal reasoning. National Conference on Artificial Intelligence. 524–528.115 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.