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latent-diffusion-models

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Unlock the potential of latent diffusion models with MNIST! 🚀 Dive into reconstructing and generating digits using cutting-edge techniques like Autoencoders with Channel Attention Blocks and DDPMs. Perfect for enthusiasts of computer vision, deep learning, and generative modeling! 🌌✨

  • Updated Jan 6, 2025
  • Jupyter Notebook

Official PyTorch implementation of "Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging". LDAE is a novel unsupervised framework for 3D medical imaging that combines a latent diffusion model with semantic controls.

  • Updated Apr 30, 2025
  • Jupyter Notebook

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