Project Grant 2230693
- The University of California, Davis was awarded a $600,000 project grant from the National Science Foundation Division of Information and Intelligent Systems. The grant supports the collaborative research project "SELF-SUPERVISED RECOMMENDER SYSTEM LEARNING WITH APPLICATION SPECIFIC ADAPTION" from October 15, 2021 to September 30, 2025 under the Computer and Information Science and Engineering program (CFDA 47.070). This project aims to develop self-supervised recommender system...
- This Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $1,127,925 to Carnegie Mellon University for research titled "Foundations of Self-Supervised Learning through the Lens of Probabilistic Generative Models." The research aims to develop scientific and mathematical foundations for self-supervised learning by analyzing aspects...
- This $600,000 project grant, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, will support research to develop a new Bayesian diffusion model framework for advanced visual perception and cognition systems. The University of California, San Diego (UCSD) will serve as the primary awardee, with the goal of revisiting the analysis-by-synthesis methodology by integrating generative priors into the learning and inference...
- The University of California, Davis received a $328,084 Project Grant award from the National Science Foundation Division of Computer and Network Systems on July 1, 2021. The grant supports research under the Computer and Information Science and Engineering program (CFDA 47.070) to advance the evolution of computer vision for low power devices and break through existing power and computational complexity barriers. Specifically, the university will conduct investigator-initiated research...
- This federal Project Grant award of $175,000.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development of new theoretical frameworks for self-supervised representation learning and their applications in biomedical research. The project aims to advance the theoretical foundations of this machine learning approach and expand its use in biomedical domains where labeled data is scarce. Key anticipated outcomes include new...
- This National Science Foundation award provided $332,659 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the University of Wisconsin-Madison from September 2021 through March 2023. The funding supported research activities to advance weakly-supervised visual scene understanding through combining images and videos to go beyond semantic tags. As part of the Computer and Information Science and Engineering program's goals to support...
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the University of California, San Diego (UCSD) under the Computer and Information Science and Engineering (CFDA 47.070) program. The 3-year grant, effective July 1, 2023, supports research to develop dynamic neural network architectures that can efficiently enable multimodal perception, including vision, audio, and language processing. The research aims to address...
- The University of California, Davis received a $382,629 Project Grant award from the National Science Foundation Division of Information and Intelligent Systems on August 15, 2021 to support research through July 31, 2022. The grant funds the development of an extensible heterogeneous network embedding framework to enable application-specific adaptation under the Computer and Information Science and Engineering program (CFDA #47.070). This framework will provide customizable network...
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program totaling $174,604 is focused on advancing the field of robotic visual perception. The project aims to address critical limitations in current artificial intelligence systems, particularly their inability to generalize effectively to novel environments and human-centered interactions. To accomplish this, the project proposes two main thrusts: human-centered...
- This $400,000 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a principled and unified mathematical framework for deep learning on low-dimensional data structures. The project aims to bridge the gap between theory and practice of deep learning by designing "white-box" deep neural networks using unrolled optimization schemes to maximize information gain in...
This Project Grant from the National Science Foundation Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $169,938 to support research in self-supervised visual representation learning using mixed labeled and unlabeled data. Specifically, the University of California, Davis will study novel self-supervised learning algorithms that can learn rich visual features from unlabeled images and videos by modeling regularities within natural image and video spaces. The university will also examine a multi-task learning framework to aggregate knowledge from multiple supervised and self-supervised learning methods using quantization to generalize representations across visual recognition tasks such as object detection and action recognition. The one-year project commenced on October 1, 2021 and is scheduled to conclude on August 31, 2022.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $85.0k | 6/2/22 |