Project Grant 2310632
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $184,593 project grant to Lafayette College in Easton, Pennsylvania. The grant, under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), will fund collaborative research to develop theoretical tools and efficient numerical methods for solving the optimal transport problem. This mathematical problem seeks to minimize the total cost of transporting mass from one location to another, with applications...
- This three-year project grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) provides $378,158 to Carnegie Mellon University to develop mathematical tools for data science and signal processing applications. Specifically, the awardee will investigate transportation-based geometries and gradient flows to provide sampling methods that leverage data geometry and can be accurately approximated in high dimensions. They will study ensemble methods...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will provide $160,000 to Cornell University from July 1, 2024 to June 30, 2027 to advance statistical optimal transport theory and its applications. The research project aims to develop new computational and statistical methods for optimal transport, and apply them to various data analysis tasks like clustering, generative modeling, and dimension reduction for...
- This National Science Foundation Project Grant award of $540,000 provides funding from July 1, 2022 to June 30, 2025 to address new challenges in statistical inference with regularized optimal transport. The award is made under the Mathematical and Physical Sciences program (CFDA 47.049) to Cornell University to explore modern regularization techniques for optimal transport distances and develop a comprehensive statistical theory to facilitate principled inference in high dimensions....
- The National Science Foundation awarded a $239,999 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation from September 15, 2022 to August 31, 2025. The grant funds research to develop mathematical theories and efficient algorithms for multi-marginal optimal transport problems with graphical costs. Specifically, the principal investigator will establish a unified framework for these problems by merging concepts from optimal...
- This three-year, $631,860 project grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program, will support the development of efficient algorithms for optimal transport in geometric settings. The researchers at Duke University will advance theoretical understanding of optimal transport and bridge gaps between theory and practice of algorithm development. They will exploit combinatorial,...
- This National Science Foundation Project Grant of $229,021 awarded on August 1, 2022 will support research at the University of Texas at Austin to develop mathematical frameworks in optimal transport applications to probability, machine learning, and kinetic theory through July 31, 2025. Under the Mathematical and Physical Sciences program (CFDA 47.049), the investigator will advance understanding of stochastic modeling, artificial intelligence algorithms, and kinetic theory by exploiting...
- This National Science Foundation Project Grant of $315,519 supports research at the University of California, Los Angeles from July 2022 to June 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The award funds research investigating challenging problems in optimal transport theory and its applications in fields including partial differential equations, geometry, probability, and machine learning. Key areas of focus include developing the theory to analyze games with large...
- This three-year Project Grant from the National Science Foundation's Mathematical and Physical Sciences program, totaling $399,998, will fund research at Cornell University's Office of Sponsored Programs on statistical optimal transport in high dimensional mixtures. Specifically, the researchers will define a new "sketched Wasserstein distance" measure to compare and analyze high-dimensional datasets arising in fields such as linguistics, computational biology, and particle physics....
- The National Science Foundation (NSF) has awarded a $1,474,838 Project Grant under its Mathematical and Physical Sciences (CFDA 47.049) program to Carnegie Mellon University (CMU) to support the "Frontiers in Applied Analysis" Research Traineeship (RTG) program. This 5-year grant, starting on September 1, 2024, will create a rich ecosystem of research and training activities focused on applied analysis, encompassing areas such as partial differential equations, calculus of...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $600,000 Project Grant to Carnegie Mellon University (CMU) under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports a 3-year research project focused on developing rigorous statistical methods for Optimal Transport, a mathematical technique used to combine data from different scientific domains and mitigate unintended biases in algorithms. The project has three main thrusts: 1) constructing central limit theorems and confidence intervals for estimated transport maps, 2) deriving more efficient transport maps, and 3) applying the methods to particle physics data analysis problems, including estimating background distributions, quantifying systematic uncertainty, and decorrelating signal classifiers. The project will also train graduate students as part of the research activities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $600.0k | 8/14/23 |