🙏 Please help us improve the SBI toolbox! 🙏
In preparation for the SBI Hackathon, we’re running a user study to learn what we can improve and how we can grow.
👉 Please share your thoughts here: https://t.co/axxd06ixVR
Your input will make a big difference—thank you! 🙌
Interested to learn more? Come visit our poster at #Neurips2024, or simply get in touch! Huge thanks again to Juius Vetter, @CorSchroeder@_rdgao , and @jakhmack
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Julius Vetter (on Bluesky) and I are excited to present our work at #Neurips2024! We present Sourcerer: a maximum-entropy, sample-based solution to source distribution estimation.
Paper: https://t.co/HUYgz8ySCw
Code: https://t.co/WBPD3uVQUm
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We apply Sourcerer to a real dataset of single-neuron recordings and the Hodgkin-Huxley model. This model is misspecified and highly nonlinear. Still, Sourcerer estimates source distributions that accurately reproduce the dataset, again achieving higher entropy “for free”!
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Thrilled to announce we have three #NeurIPS2024 papers! Interested in simulating realistic neural data with diffusion models or recurrent neural networks, or in source distribution sorcery? Have a look 👇 1/4
We introduce a new maximum-entropy, sample-based approach to solve the source distribution estimation problem. Poster #4006 (East; Fri 13 Dec 11:00 PT). By Julius Vetter, @guymoss13, ➡️https://t.co/sKtS35cj9F 4/4
The sbi package is growing into a community project 🌎 To reflect this and the algorithms, neural nets, and diagnostics that have been added since its initial release, we have written a new software paper. Reach out if you want to get involved: https://t.co/IKRLTONnbj
A propos: Inspired to do a PhD or Postdoc in #ML4Science/#AI4Science? We have multiple openings to work ML and AI tools for scientific discovery, in neuroscience and beyond!
Full details: https://t.co/oNwIeQ3g8v
Students: Apply by Nov 15, directly to IMPRS-IS or @ELLISforEurope
I hacked together a semantic search engine for ICLR 2025 paper submissions! 🔍📄
Uses OpenAI embeddings and BM25 reranking.
Anecdotally, it feels much more useful than the OpenReview search button! Try it out now: https://t.co/l61nW1Cyj6
(Fun fact, I did not write a single line of non-python code. @cursor_ai is insanely powerful🧠)
We’re at Bernstein Conference next week with lots of new work to share: 10 posters, 1 workshop talk, and don’t miss @jakhmack’s invited talk on Wednesday!
If you’re excited about machine learning for (neuro)science, come chat with us—we’re hiring PhD students & postdocs!
We’re stoked to share: “A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science”.
Now out in TMLR: https://t.co/FNmK52nGkG
This was an incredibly special project for us, as it involved the **entire** lab getting together!
Puh, we have been preparing the new release of the sbi toolbox for quite a while now, and I am really glad to see it out now! Have a look, there are a lot of cool new features! 🚀
We just released a new version of `sbi`, and this one has _a ton_ of new features! Many of these features are thanks to more than 30 (mostly new) contributors. We are very excited about the growing community and the new release! 🧵 1/8
We’re excited to share that the SBI package is now officially @NumFOCUS affiliated and growing into a community project. A lot of upcoming release originated from a hackathon earlier this year, and there are more events planned soon. Stay tuned for details! #opensource#hackathon