This study explores the representation learning abilities of Denoising Diffusion Models (DDM) and finds that only a few modern components are critical for learning good representations, leading to a simplified approach resembling a classical Denoising Autoencoder (DAE).

https://arxiv.org/abs//2401.14404

YouTube: https://www.youtube.com/@ArxivPapers

TikTok: https://www.tiktok.com/@arxiv_papers

Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016

Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers