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Lukas Schumacher

@schumacherlu.bsky.social

199 followers 377 following 2 posts

Postdoctoral Researcher at University of Basel Interested in Cognitive Modeling | Decision Making | Dynamics in Cognition | Amortized Bayesian Inference | Superstatistics

Posts Replies Media

Reposted by Lukas Schumacher

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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Reposted by Lukas Schumacher

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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Reposted by Lukas Schumacher

Approximate Bayes Seminar @approxbayesseminar.bsky.social · 14/01/2025

Paul Bürkner (TU Dortmund University), will give our next talk. This will be about "Amortized Mixture and Multilevel Models", and is scheduled on Thursday the 30th January at 11am. To receive the link to join, sign up at listserv.csv.warwick...

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Reposted by Lukas Schumacher

Marvin Schmitt @marvin-schmitt.com · 06/12/2024

Check out this project on modeling stationary and time-varying parameters with BayesFlow. The family of methods is called "neural superstatistics", how can it not be cool!? 😎 👨‍💻 Led by @schumacherlu.bsky.social

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Reposted by Lukas Schumacher

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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