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fid

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mplementation and study of deep generative models including VAE, GAN, and Diffusion. Explores latent representation learning, sampling, and reconstruction using PyTorch. Includes experiments on image generation, comparison of architectures, and evaluation via FID/IS metrics.

  • Updated Oct 16, 2025
  • Jupyter Notebook

Parameter-efficient optimization of conditional diffusion models using multi-resolution attention, classifier-free guidance ablation, and DDIM sampling — achieving 17% FID improvement with 85% reduced training time.

  • Updated Mar 3, 2026
  • Jupyter Notebook

This repository hosts the codebase for the conference paper titled "Denoising diffusion probabilistic model for generating histopathology images".

  • Updated Jul 17, 2025
  • Jupyter Notebook

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