2023 Fiscal Year Research-status Report
On Optimal Transport-based Statistical Measures for Graph Structured Data and Applications
| Project/Area Number |
23K16939
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| Research Institution | University of Tsukuba |
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Principal Investigator |
NGUYEN DAIHAI 筑波大学, システム情報系, 助教 (50968401)
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| Project Period (FY) |
2023-04-01 – 2026-03-31
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| Keywords | Generative models / Constrained domains / optimal transport |
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| Outline of Annual Research Achievements |
The research aims to develop optimal transport-based learning models for structured data, along with their related extensions and applications.
This year, our main focus has been on learning to generate structured data. Generating structured data, such as graphs, poses a significant challenge due to the constraints imposed on the generated samples. To address it, we formulated the problem of generating structured data as a distribution optimization problem on constrained domains. Then we developed a general framework based on the optimal transport theory to tackle this issue. We conducted an analysis of theoretical properties and convergence of the proposed, as well as experiments on synthetic and real world data sets to demonstrate its effectiveness in generating constrained samples.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
We have achieved promising results in the topics of learning to generate structured data, with our research findings being published in top conferences and journals. Moving forward, we plan to further extend our research focus to include graph data and its applications.
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| Strategy for Future Research Activity |
This year, our plan is to continue our efforts in developing optimal transport-based learning models tailored for graph-structured data, with a specific focus on their applications in Bioinformatics. Our research will encompass various domains within Bioinformatics, including molecular graphs, biological network data, and more.
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| Causes of Carryover |
The incurring amount to be used next fiscal year is due to the purchase of items not yet required. We will use them this year as originally planned for the previous fiscal year.
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Research Products
(4 results)
