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Deep Learning
A technique training generative models via continuous normalizing flows, potentially faster than diffusion.
Detailed Explanation
Flow Matching is a training method for generative models that leverages continuous normalizing flows. By directly learning the transformation between data and latent space, it enables efficient and stable sampling. This approach can accelerate training and generation processes, often outperforming traditional diffusion models in speed, making it a promising technique for high-quality, fast generative modeling in deep learning applications.
Use Cases
- •Use case: Rapidly generate high-quality images for real-time applications like video game graphics rendering.
Related Terms
Other terms in the Deep Learning category