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BayesFlow

@bayesflow.org
1.3K followers 161 following 18 posts

Amortized Bayesian Workflows in Python. 🎲 Post author sampled from a multinomial distribution, choices ⋅ @stefanradev.bsky.social ⋅ @paulbuerkner.com ⋅ @jerrymhuang.bsky.social 🔗 GitHub github.com/bayesflow-org/bayesflow 💬 Forum discuss.bayesflow.org

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BayesFlow @bayesflow.org · 12/06/2026
Check out the new baygent skill @alex-andorra.bsky.social and I wrote to automate your amortized workflows! 🚀 learnbayesstats.com/blog-posts/a...
learnbayesstats.com
Train Once, Infer a Million Times: Bayesian Inference That's (Finally) Cheap at Query Time
MCMC re-runs from scratch on every new dataset. Amortized Bayesian inference pays the cost once -- then gives you a posterior in milliseconds, forever. Stefan Radev (BayesFlow creator) and I built an ...
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psteinb.bsky.social @psteinb.bsky.social · 09/06/2026
Had a blast running a workshop on “Open challenges in SBI” with @helmholtzai.bsky.social yesterday. #HAICON26 The great @deismic.bsky.social shared his views on the genesis of SBI & its future! Posters demoed breadth of SBI uses. Thanks to all who contributed! @sbi-devs.bsky.social @bayesflow.org
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BayesFlow @bayesflow.org · 03/02/2026
On Feb 9, Jonas Arruda and @alex-andorra.bsky.social will give a live demo on diffusion models for SBI using BayesFlow. Don't miss out! www.linkedin.com/feed/update/...
linkedin.com
Diffusion Models in Python: Live Demo with Alexandre Andorra | Alexandre Andorra
📢 Big News: We are going LIVE with code! Diffusion models aren't just for generating images -- they are a powerful tool for scientific inference. On Feb 9, I’m hosting Jonas Arruda on the Learning Ba...
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BayesFlow @bayesflow.org · 02/01/2026
Diffusion models & flow matching are reshaping simulation-based inference. Thus, we wrote the first tutorial review on diffusion-based SBI. For an overview or a deep dive, check it out and let us know what you think: arXiv: arxiv.org/abs/2512.20685 Web: bayesflow-org.github.io/diffusion-ex...
arxiv.org
Diffusion Models in Simulation-Based Inference: A Tutorial Review
Diffusion models have recently emerged as powerful learners for simulation-based inference (SBI), enabling fast and accurate estimation of latent parameters from simulated and real data. Their score-b...
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BayesFlow @bayesflow.org · 15/09/2025
Simulations are no longer just “nice to have.” They’re reshaping how we do statistics. Care to learn more? Check out our paper arxiv.org/abs/2503.24011, accepted for publication in the upcoming theme issue of Philosophical Transactions A.
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NumFOCUS @numfocus.bsky.social · 13/08/2025
BayesFlow released version 2.0.4, presented numerous findings at the MathPsych/ICCM 2025 conference at Ohio State University, and expanded its contributor list to 25 active members! Congrats to BayesFlow on all these new huge accomplishments!
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BayesFlow @bayesflow.org · 30/05/2025
🧠 Check out the classic examples from Bayesian Cognitive Modeling: A Practical Course (Lee & Wagenmakers, 2013), translated into step-by-step tutorials with BayesFlow! Interactive version: kucharssim.github.io/bayesflow-co... PDF: osf.io/preprints/ps...
kucharssim.github.io
Introduction – Amortized Bayesian Cognitive Modeling
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BayesFlow @bayesflow.org · 11/02/2025
Finite mixture models are useful when data comes from multiple latent processes. BayesFlow allows: • Approximating the joint posterior of model parameters and mixture indicators • Inferences for independent and dependent mixtures • Amortization for fast and accurate estimation 📄 Preprint 💻 Code
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BayesFlow @bayesflow.org · 22/11/2024
BayesFlow is a library for amortized Bayesian inference with neural networks. ⋅ Multi-backend via Keras 3: Use PyTorch, TensorFlow, or JAX. ⋅ Modern nets: Flow matching, diffusion, consistency models, normalizing flows, transformers ⋅ Built-in diagnostics and plotting 🔗 github.com/bayesflow-or...
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BayesFlow @bayesflow.org · 03/02/2025
A study with 5M+ data points explores the link between cognitive parameters and socioeconomic outcomes: The stability of processing speed was the strongest predictor. BayesFlow facilitated efficient inference for complex decision-making models, scaling Bayesian workflows to big data. 🔗Paper
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BayesFlow @bayesflow.org · 28/01/2025
Join us this Thursday for a talk on efficient mixture and multilevel models with neural networks by @paulbuerkner.com at the new @approxbayesseminar.bsky.social!
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BayesFlow @bayesflow.org · 10/12/2024
1️⃣ An agent-based model simulates a dynamic population of professional speed climbers. 2️⃣ BayesFlow handles amortized parameter estimation in the SBI setting. 📣 Shoutout to @masonyoungblood.bsky.social & @sampassmore.bsky.social 📄 Preprint: osf.io/preprints/ps... 💻 Code: github.com/masonyoungbl...
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BayesFlow @bayesflow.org · 06/12/2024
Neural superstatistics are a framework for probabilistic models with time-varying parameters: ⋅ Joint estimation of stationary and time-varying parameters ⋅ Amortized parameter inference and model comparison ⋅ Multi-horizon predictions and leave-future-out CV 📄 Paper 1 📄 Paper 2 💻 BayesFlow Code
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BayesFlow @bayesflow.org · 25/11/2024
Any single analysis hides an iceberg of uncertainty. Sensitivity-aware amortized inference explores the iceberg: ⋅ Test alternative priors, likelihoods, and data perturbations ⋅ Deep ensembles flag misspecification issues ⋅ No model refits required during inference 🔗 openreview.net/forum?id=Kxt...
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BayesFlow @bayesflow.org · 22/11/2024
To celebrate the new beginnings on Bluesky, let's reminisce about one of our highlights from the old days: The unexpected shout-out by @fchollet.bsky.social that made everyone go crazy on the BayesFlow Slack server and led to a 15% increase in GitHub stars.
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BayesFlow @bayesflow.org · 22/11/2024
BayesFlow is a library for amortized Bayesian inference with neural networks. ⋅ Multi-backend via Keras 3: Use PyTorch, TensorFlow, or JAX. ⋅ Modern nets: Flow matching, diffusion, consistency models, normalizing flows, transformers ⋅ Built-in diagnostics and plotting 🔗 github.com/bayesflow-or...
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