Bao Pham
baopham.bsky.social
Bao Pham
@baopham.bsky.social
PhD Student at RPI. Interested in Hopfield or Associative Memory models and Energy-based models.
The work is done in collaboration with Gabriel Raya, Matteo Negri, Mohammed J. Zaki, @lucamb.bsky.social , @krotov.bsky.social

Lastly, join us at Sci4DL workshop at #NeurIPS2024 to learn more!

We will be giving an oral presentation there!
December 5, 2024 at 5:29 PM
This work enables a positive perspective of spurious patterns. Unlike their usual perception in Associative Memory, such patterns play a role in signaling generalization in deep generative models, like diffusion models.

Here is a link to the paper: openreview.net/pdf?id=zVMMa....
openreview.net
December 5, 2024 at 5:29 PM
In the low training data regime (number of memories), diffusion models memorize. As the data size increases, spurious states emerge, signaling the blending of stored features into new combinations which enables generalization. This is how such models create novel outputs in the high data regime.
December 5, 2024 at 5:29 PM