Project Grant 2134237
- The University of California Santa Cruz will receive $458,486 under a two-year Project Grant from the National Science Foundation Division of Computing and Communication Foundations. The grant will fund research titled "Collaborative Research: Algebraic Framework of Compositional Functions for New Structure, Training, and Explainability of Deep Learning" from January 1, 2022 to December 31, 2024. The research aims to develop new techniques for deep learning model structure, training...
- The National Science Foundation awarded a $225,000 Project Grant to Texas A&M University under the Mathematical and Physical Sciences program (CFDA 47.049) for the period of November 1, 2021 through October 31, 2024. The grant funds collaborative research on new perspectives for deep learning by bridging approximation, statistical, and algorithmic theories. The Mathematical and Physical Sciences program aims to advance scientific knowledge and understanding in core areas of mathematics and...
- Award Summary The University of Texas at Austin received a $399,998 Project Grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for the period August 1, 2025 through July 31, 2028. The award supports research on "Numerical Scheme-Guided Deep Learning for Scientific Computing," which develops innovative algorithms that integrate classical numerical schemes with deep learning paradigms to...
- This $329,432 federal Project Grant award, provided by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), aims to enhance the research and training capacity in scientific machine learning (SciML) for undergraduate students at Texas A&M University-San Antonio (A&M-SA), a Hispanic-serving and primarily undergraduate institution. The key products and services to be delivered under this grant include: Formalizing a research partnership between...
- The National Science Foundation Office of Advanced Cyberinfrastructure awarded the University of Texas at Austin a $1.2 million Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) from September 1, 2022 to August 31, 2025. The grant funds research to develop a rigorous and reliable scientific deep learning framework for forward, inverse, and uncertainty quantification problems in computational science and engineering. Specific objectives include...
- The National Science Foundation Division of Mathematical Sciences awarded a $650,000 Project Grant to the University of Texas at Austin to support the CRCNS RESEARCH PROJECT: MULTIPLY AND CONQUER: REPLICA-MEAN-FIELD LIMIT FOR NEURAL NETWORKS from September 15, 2021 through August 31, 2024. This award will fund research under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in these fields and strengthen the nation's scientific enterprise....
- The University of Texas at San Antonio received a $159,996 Project Grant award from the National Science Foundation Division of Mathematical Sciences on August 1, 2021 to carry out the "DEFAULT BAYESIAN ANALYSIS OF SPATIAL DATA" project through July 31, 2024. The grant is being administered under the Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in the mathematical and physical sciences and strengthen the nation's scientific enterprise through...
- The National Science Foundation awarded a $800,000 Project Grant to the University of Texas at Austin under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support the development of a neurosymbolic program-synthesis framework that closely couples deep learning and classical symbolic methods for program synthesis. Researchers will explore new learning algorithms exposing neural models of code to explicit knowledge about program semantics....
- The University of Texas at Austin was awarded a $409,550 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The three-year award running from July 1, 2021 to June 30, 2024 will support research developing models and algorithms for optimal vision-based surveillance and exploration of complex environments. The funding will enable work advancing scientific understanding of major...
- The National Science Foundation awarded a $449,998 project grant to Carnegie Mellon University under the Mathematical and Physical Sciences program (CFDA 47.049) to support research titled "COLLABORATIVE RESEARCH: NEW PERSPECTIVES ON DEEP LEARNING: BRIDGING APPROXIMATION, STATISTICAL, AND ALGORITHMIC THEORIES" from November 1, 2021 to October 31, 2024. The grant aims to promote progress in mathematical and physical sciences by increasing scientific knowledge and understanding of...
The University of Texas at San Antonio received a two-year, $622,955 Project Grant from the National Science Foundation Division of Computing and Communication Foundations under the Mathematical and Physical Sciences program (CFDA 47.049). The grant will support research titled "Collaborative Research: Algebraic Framework of Compositional Functions for New Structure, Training, and Explainability of Deep Learning." The research aims to develop new techniques for deep learning model structure, training procedures, and explainability using an algebraic framework of compositional functions. This work has the potential to advance the mathematical and physical sciences by strengthening understanding of machine learning methods and enhancing model transparency.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $623.0k | 8/12/21 |