keishihara/flow-matching
Flow Matching implemented in PyTorch
This tool helps machine learning engineers generate high-quality synthetic data, such as images or complex 2D data distributions. You provide a target data distribution, and it generates new samples that closely match its characteristics. This is ideal for researchers and practitioners in generative modeling who need to create realistic data for training or analysis.
Use this if you need to generate synthetic data that accurately mirrors a complex real-world distribution, whether it's for augmenting datasets or exploring generative models.
Not ideal if you are looking for an out-of-the-box solution for basic data augmentation or if you don't have experience with PyTorch and generative modeling concepts.
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99
Forks
13
Language
Python
License
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Category
Last pushed
Jan 18, 2026
Commits (30d)
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