Issei Sato
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Biomedical Engineering
- Management Science and Operations Research top 5%
- Co-authors
- Hiroshi NakagawaBin YangMasashi SugiyamaRyoichi HorisakiSadao OtaShingo OnoMasataka GotoYukihiro Nomura
- Topics
- Bayesian Methods and Mixture Models (16 papers)Gaussian Processes and Bayesian Inference (12 papers)Topic Modeling (11 papers)
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Issei Sato
69 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 698
- Computer Vision and Pattern Recognition 207
- Molecular Biology 120
- Biomedical Engineering 117
- Management Science and Operations Research 98
Countries citing papers authored by Issei Sato
This map shows the geographic impact of Issei Sato'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 Issei Sato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Issei Sato more than expected).
Fields of papers citing papers by Issei Sato
This network shows the impact of papers produced by Issei Sato. 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 Issei Sato. The network helps show where Issei Sato may publish in the future.
Co-authorship network of co-authors of Issei Sato
This figure shows the co-authorship network connecting the top 25 collaborators of Issei Sato. A scholar is included among the top collaborators of Issei Sato 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 Issei Sato. Issei Sato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima | 3 |
| 3 | Solving NP-Hard Problems on Graphs by Reinforcement Learning without Domain Knowledge. | 10 |
| 4 | 170 | |
| 5 | Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling. | 2 |
| 6 | Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks | 25 |
| 7 | Analysis of Minimax Error Rate for Crowdsourcing and Its Application to Worker Clustering Model | 0 |
| 8 | Evaluating the Variance of Likelihood-Ratio Gradient Estimators | 2 |
| 9 | Variational Inference based on Robust Divergences | 3 |
| 10 | Bayesian Nonparametric Poisson Process Allocation | 0 |
| 11 | Differential Privacy without Sensitivity | 7 |
| 12 | Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP | 3 |
| 13 | Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process | 18 |
| 14 | Latent Confusion Analysis by Normalized Gamma Construction | 1 |
| 15 | 1 | |
| 16 | Multi-armed Bandit Problem with Lock-up Periods | 4 |
| 17 | Reducing Wrong Labels in Distant Supervision for Relation Extraction | 112 |
| 18 | Deterministic Single-Pass Algorithm for LDA | 13 |
| 19 | 0 | |
| 20 | Mining Semi-structure for Text with Dependency Structure | 2 |
About Issei Sato
Issei Sato is a scholar working on Acoustics and Ultrasonics, Artificial Intelligence and Statistics and Probability, having authored 75 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (16 papers), Gaussian Processes and Bayesian Inference (12 papers) and Topic Modeling (11 papers). The work is most often cited by research in Acoustics and Ultrasonics (80 citations), Artificial Intelligence (698 citations) and Biophysics (74 citations). Issei Sato has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Hiroshi Nakagawa, Bin Yang, Masashi Sugiyama, Ryoichi Horisaki, Sadao Ota, Shingo Ono, Masataka Goto, Yukihiro Nomura, Shouhei Hanaoka and Soichiro Miki. Their work appears in journals such as Science, ACM Transactions on Graphics and Sustainability.
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.