POT and SPPOT
Maintenance
10/25
Adoption
15/25
Maturity
25/25
Community
25/25
Maintenance
0/25
Adoption
4/25
Maturity
16/25
Community
0/25
Stars: 2,772
Forks: 540
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 7
Forks: —
Downloads: —
Commits (30d): 0
Language: Python
License: —
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About POT
PythonOT/POT
POT : Python Optimal Transport
This library helps data scientists and machine learning engineers analyze how two different datasets or signals can be optimally transformed to match each other. It takes in various types of data distributions (like images, signals, or feature sets) and outputs the most efficient "transport plan" or mapping between them. This is particularly useful for tasks such as comparing different image patterns or adapting models across varied data domains.
data-alignment
image-processing
machine-learning
signal-comparison
domain-adaptation
About SPPOT
rhfeiyang/SPPOT
Official implementation of 'SP$^2$OT: Semantic-Regularized Progressive Partial Optimal Transport for Imbalanced Clustering'.
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