This $160,000 Project Grant award, made by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), supports research conducted by Purdue University aimed at developing new methods for reliable uncertainty quantification in high-dimensional statistical structure learning problems. The project will create a new framework using imprecise probability to offer robust techniques for learning complex latent structures while providing valid and efficient uncertainty quantification. This research is expected to have significant impact across scientific disciplines like biomedical, physical, and social sciences where high-dimensional structure learning is ubiquitous. The award term runs from July 1, 2024 to June 30, 2027, and no subawards are planned.
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