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pouya bashivan

@PouyaBashivan

🇮🇷🇨🇦Proud husband & dad | Associate Prof @McGillPhysioloG | member @IPNMcGill @MILAMontreal | studying deep artificial/biological neural nets
Montreal, QC bashivanlab.org Joined October 2012
712 Following 1K Followers 339 Posts

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pouya bashivan @PouyaBashivan
Our work on building world models from episodic memories is accepted to #ICLR26!
Led by (then undergraduate, now masters student) @HeHerbie
Check out the tweeprint below!
Herbie He @HeHerbie Mar 18
New paper 🚨 #ICLR26

Most world models predict the future from a past trajectory. But neuroscience suggests that such inference can instead be made from temporally independent experiences.

We built the Episodic Spatial World Model (ESWM), a model that does exactly this:
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pouya bashivan @PouyaBashivan
I'm looking for a PhD student in my lab. Mila is one of the best academic AI research institutions with a strong neuroAI community. Please apply to if you are interested!
Mila - Institut québécois d'IA Verified account @Mila_Quebec Oct 15
Mila's annual supervision request process is now open to receive MSc and PhD applications for Fall 2027 admission! For more information, visit mila.quebec/en/prospective…
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pouya bashivan @PouyaBashivan
Do you have any fun memories from past CCN conferences? Please share your experiences and any photos you have from previous CCNs! We are organizing an event for #CCN2026 to remember previous years.
CogCompNeuro @CogCompNeuro Jul 8
CCN began at Columbia in 2017. As #CCN2026 returns to NY, a special Back2NY event will feature a crowd-sourced panel discussion on how the community has grown, prior challenges, and future perspectives.

Share your experiences in the community survey: 2026.ccneuro.org/back2ny/
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pouya bashivan @PouyaBashivan
So proud of this work co-led by @aspa1313 and @johanobandoc
Fantastic collaboration with @AaronCourville & @pcastr
Tldr; Constraining representations within isotropic Gaussian distribution massively improves performance during RL!
New paper 🚨
"Stable Deep Reinforcement Learning via Isotropic Gaussian Representations"

Deep RL suffers from unstable training, representation collapse, and neuron dormancy. We show that a simple geometric insight, isotropic Gaussian representations, can fix this. Here's how 👇
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