Chapter 10. Bayesian Inference and Probabilistic Programming
Mathematics is a big space of which humans so far have only charted a small amount. We know of countless areas in mathematics that we would like to visit, but that are not tractable computationally.
A prime reason Newtonian physics, as well as much of quantitative finance, is built around elegant but oversimplified models is that these models are easy to compute. For centuries, mathematicians have mapped small paths in the mathematical universe that they could travel down with a pen and paper. However, this all changed with the advent of modern high-performance computing. It unlocked the ability for us to explore wider spaces of mathematics and thus gain more accurate models.
In the final ...
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