"Center for Advanced Hindsight" lmao south park predicted this in back in 2010

Enough #Bayesplaining. It's time to start "deriving."

We're unifying physics and neuroscience from first principles (yes, really).

Come argue with me tomorrow @ 11 AM.

@neuripsconf.bsky.social
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Here's the poster info again:

📅 Wed, Dec 3, 11 AM — 2 PM
📍 Exhibit Hall C,D,E #500
🔗 neurips.cc/virtual/2025...

See you in sunny San Diego! 🌞

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✅ What's new in the paper:

We substantially improved the framing and clarity of our contributions (genuinely grateful to our amazing reviewers and their useful feedback 🙌).

+ Several new experiments (highlighted below), including scaling iP-VAE to complex color image datasets like CelebA.

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GitHub - hadivafaii/IterativeVAE: The Official PyTorch Implementation of "Brain-like Variational Inference" (NeurIPS 2025 Paper) The Official PyTorch Implementation of "Brain-like Variational Inference" (NeurIPS 2025 Paper) - hadivafaii/IterativeVAE

Final versions of paper & code:

📜 Paper: openreview.net/forum?id=573...
💻 Code: github.com/hadivafaii/I...

✅ What's new in the code:

We added a stand-alone Colab notebook implementation — a great starting point if you want to understand the iP-VAE model and train your own.

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I will be at @neuripsconf.bsky.social Dec 2-8 to present our "Brain-like Variational Inference" paper 👇

Let's connect if you enjoy first-principles thinking and brain-inspired AI 🧠 🤖

Poster info:
📅 Wed, Dec 3, 11 AM — 2 PM
📍Exhibit Hall C,D,E #500
🔗 neurips.cc/virtual/2025...

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Natural Gradient Works Efficiently in Learning Abstract. When a parameter space has a certain underlying structure, the ordinary gradient of a function does not represent its steepest direction, but the natural gradient does. Information geometry ...

This one is an all time favorite of mine:

direct.mit.edu/neco/article...

(tho maybe not that relevant to the "rescue" thing)

Thanks @hadivafaii.bsky.social for the invitation! x.com/hadivafaii/s...

The neuron as a direct data-driven controller (DD-DC) by Moore et al., 2024 We explored DD-DC, a provocative normative theory proposing that neurons are not just information processors, but active feedback controllers that steer their environment—including other neurons—towar...

🔗 Meeting summary: sensorimotorai.github.io/2025/11/20/d...
📜 Read the paper: www.pnas.org/doi/10.1073/...
💬 Join the conversation on Slack: join.slack.com/t/sensorimot...

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💡 The killer insight: biological "quirks" are actually optimal control solutions:

🔷 STDP = solving the LQR cost (learning causal impact from feedback)
🔷 Noise = stabilizing "persistence of excitation"
🔷 ReLU = optimal policy to cross unstable fixed points

Conclusion:
✅ Agency is cellular.

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Stop treating neurons as passive processors... They are active controllers! 🧠 🎮

In our latest Journal Club session, Thelonious Cooper presented "The neuron as a direct data-driven controller" by Moore et al., with special commentary from Mitya Chklovskii.

🎥 www.youtube.com/watch?v=0P7k...

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NeurIPS 2025:

bsky.app/profile/hadi...

RL Debates 5: Anne “not everything is RL” Collins In our 5th RL Debates presentation, Anne argued that reward-based learning is not always driven by RL computations. Sometimes it’s working memory combined with outcome-insensitive habit formation, mim...

Additional links:

📝 Meeting summary: sensorimotorai.github.io/2025/11/13/a...
📅 Future meetings: sensorimotorai.github.io/schedule/
💬 Join the conversation on Slack: join.slack.com/t/sensorimot...

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RL Debates 5: Anne "not everything is RL" Collins

Anne delivered an amazing synthesis of her extensive work on how working memory shapes reward-based learning in humans.

📜 Read the paper: nature.com/articles/s41...
📽️ Watch the full presentation: www.youtube.com/watch?v=eEqZ...

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RL Debates 4: Adam “I literally measured value in the brain” Lowet In our 4th RL Debates presentation, Adam presented broad topics on RL and the brain, including his distributional RL paper.

Additional links:

📝 Meeting summary: sensorimotorai.github.io/2025/novembe...
📅 Future meetings: sensorimotorai.github.io/schedule/
💬 Join the conversation on Slack: join.slack.com/t/sensorimot...

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RL Debates 4: Adam "I literally measured value in the brain" Lowet

Adam's talk covered a lot of ground — from his recent work on distributional RL (nature.com/articles/s41...) to a broader discussion of RL & the brain.

📽️ Watch the full meeting here: www.youtube.com/watch?v=Xe7B...

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Cover of the book “the brain abstracted” by M Chirimuuta

A passage from chapter 1 including the quote

Picked this one up for reading over the holidays.

“The thesis of this book is that the dominant ideas that have shaped #neuroscience are best understood as attempts to simplify the brain.” 🧠

…which is itself a simplification 😂

An opponent striatal circuit for distributional reinforcement learning - Nature D1- and D2-expressing striatal neurons encode separate parts of a learned reward distribution, paralleling modern approaches in machine learning.

📅 Next meeting: November 6, 9:00 AM PT

Where Adam Lowet will present his paper on distributional RL in brain: nature.com/articles/s41...

- See the full schedule here: sensorimotorai.github.io/schedule/
- Join our Slack: join.slack.com/t/sensorimot...

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Schedule Monthly journal club and RL Debate Series

📜 Read the summary post: sensorimotorai.github.io/schedule/

@cortical-canonical.bsky.social @thousandbrains.org

RL Debates 3: Niels "you have 1000 brains in your brain" Leadholm

See how Monty (a cortex-inspired model), crushes powerful ViTs in out-of-distribution & continual learning tasks—all while being millions of times more efficient in data & FLOPs!

📽️ Watch here: www.youtube.com/watch?v=Q0FF...

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Schedule Monthly journal club and RL Debate Series

Next Thursday (Oct 23) Niels Leadholm from @thousandbrains.org will present.

- See the full schedule here: sensorimotorai.github.io/schedule/

- Join our Slack: join.slack.com/t/sensorimot...

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Frontiers | Learning and exploration in action-perception loops Discovering the structure underlying observed data is a recurring problem in machine learning with important applications in neuroscience. It is also a prima...

Also, fun fact: Fritz's paper (frontiersin.org/journals/neu...) talks about world modeling in 2013, way before it was cool.

You can hear at 49:01 (youtube.com/watch?v=rlF-...), he's describing an agent that runs an "internal simulation" of the world to decide its next action.

RL Debates 2: Fritz "learning for the sake of learning" Sommer

Fritz introduced an information-theoretic, first-principles approach to modeling exploration through the maximization of "predicted information gain."

📽️ Watch the full presentation here: www.youtube.com/watch?v=rlF-...

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Thank you!

A new user influx - welcome! A great nudge to pass this around. (Psst: Scientist authors tend to have fascinating Bsky feeds).

go.bsky.app/2LmKSDN

Can I also join? I still haven't written a book, but definitely planning to. I've started with blog posts, where I break down difficult technical concepts and make the accessible:

- World Models, Adaptation, and Surprise: bsky.app/profile/hadi...

- Perception as Inference: bsky.app/profile/hadi...

We started our RL debate series!
www.youtube.com/watch?v=E0A0...

Wonderful to see this high-level conversation about reinforcement learning happen not just “at the top” but across many professional levels (including trainees). 👏👏👏 to everyone involved. Such a thoughtful way to expedite progress. I look forward to following along.

I'm excited to announce that we've added two more contenders to the RL Debate Series!

- Anne Collins (Professor @ucberkeleyofficial.bsky.social)
- Niels Leadholm (Research Manager @thousandbrains.org)

Things are heating up!!

See the flyer for details👇

🌎 sensorimotorai.github.io/debates/

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Join Sensorimotor AI on Slack Slack is a new way to communicate with your team. It’s faster, better organized, and more secure than email.

Join us on Slack: join.slack.com/t/sensorimot...

More info on our website: sensorimotorai.github.io

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