ermongroup/ncsnv2
The official PyTorch implementation for NCSNv2 (NeurIPS 2020)
Score-based generative modeling that learns vector fields pointing toward high-density regions of data distributions, enabling high-resolution image synthesis without adversarial training. The architecture trains neural networks to estimate score functions across multiple noise scales, then generates samples through Langevin dynamics. Includes support for image interpolation, inpainting, and FID evaluation across PyTorch-based training pipelines configured via YAML files.
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Language
Python
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MIT
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Last pushed
Jun 12, 2021
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