Kazuho Watanabe
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Statistics and Probability top 10%
- Signal Processing
- Computational Mechanics
- Co-authors
- Sumio WatanabeKentaro KatahiraMasato OkadaKazushi IkedaShigeo TakahashiHsiang‐Yun WuIssei FujishiroShiro Ikeda
- Topics
- Bayesian Methods and Mixture Models (22 papers)Statistical Methods and Inference (10 papers)Gaussian Processes and Bayesian Inference (10 papers)
- Journals
- IEEE Transactions on Information TheoryIEEE Transactions on Neural Networks and Learning SystemsNeurocomputing
- Partner nations
- JapanGermanySwitzerland
In The Last Decade
Kazuho Watanabe
50 papers receiving 246 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 155
- Computer Vision and Pattern Recognition 61
- Statistics and Probability 42
- Signal Processing 39
- Computational Mechanics 23
Countries citing papers authored by Kazuho Watanabe
This map shows the geographic impact of Kazuho Watanabe'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 Kazuho Watanabe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kazuho Watanabe more than expected).
Fields of papers citing papers by Kazuho Watanabe
This network shows the impact of papers produced by Kazuho Watanabe. 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 Kazuho Watanabe. The network helps show where Kazuho Watanabe may publish in the future.
Co-authorship network of co-authors of Kazuho Watanabe
This figure shows the co-authorship network connecting the top 25 collaborators of Kazuho Watanabe. A scholar is included among the top collaborators of Kazuho Watanabe 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 Kazuho Watanabe. Kazuho Watanabe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | Unified Likelihood Ratio Estimation for High- to Zero-frequency N-grams | 2 |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies | 0 |
| 11 | Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP | 3 |
| 12 | 3 | |
| 13 | Packet loss rate estimation with active and passive measurements | 4 |
| 14 | 9 | |
| 15 | Phase Transition of Variational Bayes Learning in Bernoulli Mixture | 5 |
| 16 | 10 | |
| 17 | 2 | |
| 18 | Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation | 33 |
| 19 | 11 | |
| 20 | Variational Bayesian Stochastic Complexity of Mixture Models | 6 |
About Kazuho Watanabe
Kazuho Watanabe is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 53 papers that have together received 251 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (22 papers), Statistical Methods and Inference (10 papers) and Gaussian Processes and Bayesian Inference (10 papers). The work is most often cited by research in Statistics and Probability (42 citations), Artificial Intelligence (155 citations) and Signal Processing (39 citations). Kazuho Watanabe has collaborated with scholars based in Japan, Germany and Switzerland. Frequent co-authors include Sumio Watanabe, Kentaro Katahira, Masato Okada, Masato Okada, Kazushi Ikeda, Shigeo Takahashi, Hsiang‐Yun Wu, Issei Fujishiro, Shiro Ikeda and Masahiro Kobayashi. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.
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.