Thanks so much to our fantastic collaborators from the @ramdya.bsky.social lab, the whole @mackelab.bsky.social team, but in particular @vetterj.bsky.social, @rdgao.bsky.social, & @jakhmack.bsky.social, & Gonçalves lab's very own
@ppjgoncalves.bsky.social 🙏🥂 Thanks also to our reviewers & editor!

We apply our masked VAE approach to drosophila 🪰walking behavior, a macaque 🐒reach task & a synthetic dataset with access to the ground truth.

We propose calibration checks to evaluate the models’ uncertainty estimates, to avoid making confidently wrong predictions.

Check out the paper for more 🙂

We use masked VAEs to address two model desiderata in one model:

1. jointly modeling conditional distributions that are commonly targeted in neuroscience (e.g., encoding 🐭➡️🧠and decoding 🧠 ➡️🐭) and

2. accounting for low-dimensional dynamics underlying both neural activity and behavior. 🌀

LDNS ➡️ proceedings.neurips.cc/paper_files/...

Masked VAEs ➡️ www.cell.com/cell-reports...

Workshop program ➡️ neurofm-workshop.github.io

Already a bit nostalgic as this will most likely be my last conference as a PhD student — time to slowly wrap up 🎒⌛