Von Neumann on how games featuring partial information, chance, and deception will make you a better decision-maker.
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Part 1: A primer on IID, exchangeability, and Bayesian causality.
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Part 2: A primer on IID, exchangeability, and Bayesian causality.
Part 3: A primer on IID, exchangeability, and Bayesian causality.
The typical machine learning playbook and why it sucks.
If Martin Luther were a modeler, he'd have written this.
Rotation invariant Christmas trees are trending this year.
How deep causal generative modeling could address algorithmic (un)fairness
Why deep learning does so well at generating natural language, and why it doesn't.
A rough Internet guide to interventions in causal models.