Update to the README file to include diffusion autoencoder.

Signed-off-by: Virginia <virginia.fernandez@kcl.ac.uk>

generation/README.md

@@ -78,3 +78,6 @@ Examples show how to perform anomaly detection in 2D, using implicit guidance [2
 
 ## 2D super-resolution using diffusion models: [using torch](./2d_super_resolution/2d_sd_super_resolution.ipynb) and [using torch lightning](./2d_super_resolution/2d_sd_super_resolution_lightning.ipynb).
 Examples show how to perform super-resolution in 2D, using PyTorch and PyTorch Lightning.
+
+## [Guiding the synthetic process using a semantic encoder](./2d_diffusion_autoencoder/2d_diffusion_autoencoder.ipynb)
+Example shows how to train a DDPM and an encoder simultaneously, resulting in the latents of the encoder guiding the inference process of the DDPM.