Acknowledgements - All Tutorials

Written by Joe Austerweil. Thank you to Tim Burness, Grisha Szep, Kyana Burhite, Hongtao Hao, and the many students who took Human and Machine Learning over the years who have provided invaluable feedback on an early draft of this tutorial.

Thanks to amplifier, which was used to help refine the tutorial content and generate the connecting GenJAX tutorials.

Further thanks to the Japan Probabilistic Computing Consortium Association (JPCCA) for funding my ability to polish and publish this tutorial series.

Please reach out to Joe via email if you have any constructive feedback (anything from X could be more clear or this is a great resource I will share with my class).

Resources

GenJAX Documentation:

• Official docs: gen.dev
• More examples: GenJAX GitHub

Probability Theory:

• This tutorial’s probability chapters!
• Probabilistic Programming & Bayesian Methods for Hackers (free online)
• Think Bayes by Allen Downey (beginner-friendly)