Pytorch Implementations for Probabilistic Machine Learning book by Kevin Murphy.
The implementations in here are in some way a trade-off between readability, execution speed and me trying to get stuff done quickly. This means that I only had limited time to optimize the code and that e.g. stuff that I could potentially parallelize is still being iterated over using a for loop.
It's also not a collection of solutions to the exercises in the book. Instead it's a collection of algorithms from the book that I found interesting or useful to implement.
pip install .
17.4.2 Forwards Algorithm for HMMs with Gaussian likelihood
17.4.3 Forwards-Backwards Algorithm for HMMs with Gaussian likelihood