This map shows the geographic impact of Masato Okada'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 Masato Okada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masato Okada more than expected).
This network shows the impact of papers produced by Masato Okada. 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 Masato Okada. The network helps show where Masato Okada may publish in the future.
Co-authorship network of co-authors of Masato Okada
This figure shows the co-authorship network connecting the top 25 collaborators of Masato Okada.
A scholar is included among the top collaborators of Masato Okada 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 Masato Okada. Masato Okada is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Suzuki, Takayuki, et al.. (2019). せん断希薄化流体に対する粘性混合モデルの混合【JST・京大機械翻訳】. ACM Transactions on Graphics. 38(4). 1–17.1 indexed citations
9.
Okada, Masato. (2018). Sparse modeling and data driven science. The Japan Society of Applied Physics.
10.
Karakida, Ryo, Masato Okada, & Шун-ичи Амари. (2016). Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold.. The European Symposium on Artificial Neural Networks.1 indexed citations
11.
Nagata, Kenji, et al.. (2011). Application of Bayesian Estimation for XPS Data Analysis. IEICE Technical Report; IEICE Tech. Rep.. 110(476). 125–130.1 indexed citations
Sugita, Seiji, et al.. (2010). A New Modified Gaussian Model (MGM) Using the Cross-Validation Method. LPI. 1744.3 indexed citations
14.
Oizumi, Masafumi, et al.. (2008). A general framework for investigating how far the decoding process in the brain can be simplified. neural information processing systems. 21. 1225–1232.3 indexed citations
15.
Katahira, Kentaro, et al.. (2008). Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM. Neural Information Processing Systems. 21. 817–824.1 indexed citations
16.
Okada, Masato, et al.. (2008). Coarse image region segmentation using a region-based coupled MRF model and its CMOS circuit implementation. IEICE Technical Report; IEICE Tech. Rep.. 107(542). 49–54.
17.
Hamaguchi, Kosuke, Masato Okada, & Kazuyuki Aihara. (2004). Theory of localized synfire chain: characteristic propagation speed of stable spike pattern. Neural Information Processing Systems. 17. 553–560.3 indexed citations
18.
Miyawaki, Yoichi & Masato Okada. (2003). Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron?. Neural Information Processing Systems. 16. 1295–1302.2 indexed citations
19.
Murayama, T. & Masato Okada. (2002). Rate Distortion Function in the Spin Glass State: A Toy Model. arXiv (Cornell University). 15. 423–430.1 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.