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Resources
Open-source code, datasets, and tools for advancing machine learning and computer vision research.
Explore our curated collection of research artifacts, including reproducible code, pre-trained models, and benchmark datasets—freely available to support collaboration and innovation in the broader research community.
Open Calls for Papers/Participation
ICCV Tutorial "Learning Nonlinear Low-Dimensional Representations from High-Dimensional Data: From Theory to Practice", Oct 2025
VITA In the Press (selected)
Datasets
Courses
At UT Austin
At TAMU
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