Introduction โ Amortized Bayesian Cognitive Modeling
๐ง 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...
30.05.2025 14:28 โ ๐ 29 ๐ 14 ๐ฌ 0 ๐ 0
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.
๐Paper
03.02.2025 12:21 โ ๐ 19 ๐ 6 ๐ฌ 0 ๐ 0
Paul Bรผrkner (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...
14.01.2025 12:00 โ ๐ 16 ๐ 4 ๐ฌ 0 ๐ 3
making your own sourdough starter is pretty simple. Give it a go :)
10.01.2025 07:07 โ ๐ 2 ๐ 0 ๐ฌ 0 ๐ 0
Looks amazing. I recently started to bake with sourdough but with much less success...
09.01.2025 15:18 โ ๐ 1 ๐ 0 ๐ฌ 1 ๐ 0
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!? ๐
๐จโ๐ป Led by @schumacherlu.bsky.social
06.12.2024 12:25 โ ๐ 11 ๐ 3 ๐ฌ 0 ๐ 0
BayesFlow is a library for amortized Bayesian inference with neural networks.
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Multi-backend via Keras 3: Use PyTorch, TensorFlow, or JAX.
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Modern nets: Flow matching, diffusion, consistency models, normalizing flows, transformers
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Built-in diagnostics and plotting
๐ github.com/bayesflow-or...
22.11.2024 22:30 โ ๐ 107 ๐ 22 ๐ฌ 1 ๐ 0
generative models and making them faster
Running Doom Trip Records @doomtriprecords.bsky.social /// Audio Mastering Engineer
Ph.D. @ DTU Compute (Cognitive Systems)
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PhD student in Computational Statistics and Machine Learning at STOR-i CDT, Lancaster University, UK.
Research Interests: Sampling Algorithms, Bayesian Experiment Designs, Neural Amortization.
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PhD candidate Uni Freiburg
RTG Statistical Modeling in Psychology. (SMiP)
Interested in mathematical modeling of social cognition and memory, stats and coding.
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Political theorist studying democracy, ethics, & institutions. Author of Democracy for Busy People (https://press.uchicago.edu/ucp/books/book/chicago/D/bo194847654.html); more at kevinjelliott.net. Generally poasting my way through this thing
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PhD student @hein-lab.bsky.social @uni-wuerzburg.de, Learning & Decision making, fMRI, modeling, delay discounting, effort, empathy, intrinsic reward
Senior Researcher in computational cognitive science @ Center for Humanities Computing, Aarhus University.
Active inference - LLM - Reinforcement learning - Bayesian modelling | Creating a neural network library for predictive coding.
I study brains and sometimes use one.
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Computational cognitive neuroscientist @cnrs.fr ๐ง ๐ป
Inner speech, mental/motor imagery, cognitive/statistical modelling, EMG, M/EEG, open and slow science. https://lnalborczyk.github.io
Astronomer, data scientist, underqualified programmer
Senior Lecturer in Data Science and Astronomy at the University of Hertfordshire
