📍Excited to share that our paper was selected as a Spotlight at #NeurIPS2025!
arxiv.org/pdf/2410.03972
It started from a question I kept running into:
When do RNNs trained on the same task converge/diverge in their solutions?
🧵⬇️
Super happy for having been awarded an @erc.europa.eu Consolidator Grant to continue our basic neuroscience work on the neural basis for motor control and motor learning. What a great way to set things up here at Champalimaud! 🎉
🚨 Job Alert for postdocs research technicians, and PhD students in 🧵
For the oculomotor nerds out there… we’re excited to share our paired papers on precerebellar circuitry!
These two studies look at how internuclear pathways talk to the cerebellum and what that means for eye movement control. 👀🧠 #neuroskyence #science
🔥🔥🔥from @ulisespereirao.bsky.social ^^^
We took a stab at how to infer both the dynamics and control parameters of partially-observable systems.
It’s a nasty problem, but @vgeadah.bsky.social made tremendous progress, ending up with some really elegant formalisms.
In a system subject to unobserved control, can you infer both the underlying dynamics and the control objective? 🤔
A year ago, I was presenting our work at IEEE CDC on solving this problem for stochastic LQR.
arxiv.org/abs/2502.15014
Short 🧵 on the results, and how I think about them a year later.
New pre-print from our lab, by Lakshmi Govindarajan with help from Sagarika Alavilli, introducing a new type of model for studying sensory uncertainty. www.biorxiv.org/content/10.1...
Here is a summary. (1/n)