Simulation-based inference (SBI) toolkit in PyTorch. Tweeted by @deismic_ and @janfiete

Joined March 2022
From hackathon to release: sbi v0.25 is here! 🎉 What happens when dozens of SBI researchers and practitioners collaborate for a week? New inference methods, new documentation, new embedding networks, a bridge to pyro and a bridge between flow matching and score-based methods 🤯
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Two more highlights: Your sbi-trained NLE can now be wrapped into a Pyro model object for flexible hierarchical inference. And based on your feedback, we added to(device) for priors and posteriors—switching between CPU and GPU is now even easier! 6/7
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sbi 0.24.0 is out! 🎉 This comes with important new features: - 🎯 Score-based i.i.d sampling - 🔀 Simultaneous estimation of multiple discrete and continuous parameters or data. - 📊: mini-sbibm for quick benchmarking Just in time for our 1-week SBI hackathon starting tomorrow!
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🙏 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: forms.gle/foHK7myV2oaK1NU57 Your input will make a big difference—thank you! 🙌
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🚀 Join the 4th SBI Hackathon! 🚀 The last hackathon was a fantastic milestone in forming a collaborative open-source community around SBI. Be part of it this year as we build on that momentum! 📅 March 17–21, 2025 📍 Tübingen or remote 👉 Details: github.com/sbi-dev/sbi/discu… 🧵👇
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What to expect: - Coding sessions to enhance the sbi toolbox - Research talks & lightning talks - Networking & idea exchange In-person attendance is encouraged but a remote option is available. Free to attend, but seats are limited. Beginners welcome! 🤗
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🎉 Just in time for the end of the year, we’ve released a new version of sbi! 📦 v0.23.3 comes with exciting features, bug fixes, and docs updates to make SBI smoother and more robust. Check it out! 👇 🔗 Full changelog: github.com/sbi-dev/sbi/relea…
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✨ Highlights in v0.23.3: - sbi is now available via @condaforge 🛠️ - we now support MCMC sampling with multiple i.i.d. conditions 🎯 (this is for you, decision-making researchers) 💡 Plus, improved docs here and there, clarified SNPE-A behavior, and a couple of bug fixes.
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🙌 Huge thanks to our contributors for this release, including 5 first-time contributors! 🌟 Special shoutout to: emmanuel-ferdman, CompiledAtBirth, tvwenger, matthewfeickert, and manuel-morales-a 🎉 Let us know what you think of the new version!
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We are launching an SBI Discord Server! 🎉 We want to use this server to further build a community around SBI, i.e., for sharing insights, questions and events around SBI in general and the sbi package in particular. You are all invited to join! 🤗 github.com/sbi-dev/sbi/discu…
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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: arxiv.org/abs/2411.17337
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For all steps of the inference process, the sbi toolbox supports strong defaults if needed, but also provides full flexibility if desired. For example, you can use a pre-configured training loop, or you can write it yourself.
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