Keiji Kanazawa
- Artificial Intelligence top 1%
- Signal Processing top 5%
- Management Science and Operations Research top 5%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Thomas DeanStuart RussellDaphne KollerT.S. HuangTaraneh DeanJohn P. ShewchukChao-Lin LiuMichael P. Wellman
- Topics
- Bayesian Modeling and Causal Inference (12 papers)Logic, Reasoning, and Knowledge (8 papers)AI-based Problem Solving and Planning (5 papers)
- Journals
- Machine LearningComputational IntelligenceIEEE Transactions on Systems Man and Cybernetics
- Partner nations
- United States
In The Last Decade
Keiji Kanazawa
14 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 1.1k
- Signal Processing 209
- Management Science and Operations Research 138
- Computational Theory and Mathematics 128
- Computer Networks and Communications 117
Countries citing papers authored by Keiji Kanazawa
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).
Fields of papers citing papers by Keiji Kanazawa
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.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 233 | |
| 4 | Local learning in probabilistic networks with hidden variables | 89 |
| 5 | The BATmobile: towards a Bayesian automated taxi | 120 |
| 6 | Sensible decisions: toward a theory of decision-theoretic information invariants | 1 |
| 7 | A Decision-Theoretic Abductive Basis for Planning* | 8 |
| 8 | Reasoning about time and probability | 14 |
| 9 | A logic and time nets for probabilistic inference | 27 |
| 10 | A model for projection and action | 35 |
| 11 | Investigations of Model-Preference Defaults | 1 |
| 12 | A model for reasoning about persistence and causationbreakdown → | 620 |
| 13 | 13 | |
| 14 | Probabilistic temporal reasoning | 115 |
About Keiji Kanazawa
Keiji Kanazawa is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 14 papers that have together received 1.3k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (12 papers), Logic, Reasoning, and Knowledge (8 papers) and AI-based Problem Solving and Planning (5 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Signal Processing (209 citations) and Software (49 citations). Keiji Kanazawa has collaborated with scholars based in United States. Frequent co-authors include Thomas Dean, Stuart Russell, Daphne Koller, T.S. Huang, Taraneh Dean, John P. Shewchuk, Chao-Lin Liu, Michael P. Wellman, Mark Boddy and Robert P. Goldman. Their work appears in journals such as Machine Learning, Computational Intelligence and IEEE Transactions on Systems Man and Cybernetics.
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.