Time series inference implemented in TensorFlow Probability

Many problems in genomics can be mapped to a time series problem. Here I illustrate how approaches from time series analysis, such as particle filters and hidden markov models, can be applied to genomics "time-series" data to make inferences about natural selection.

1. Bayesian inference (particle filter)
2. Hidden Markov Model (trained in an unsupervised manner)