Interpreting lion behaviour with nonparametric probabilistic programs
We consider the problem of unsupervised learning of meaningful behavioural segments of high-dimensional time-series observations, collected from a pride of African lions. We demonstrate, by way of probabilistic programming, a methodology which allows for quick iteration over models and Bayesian infe...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Conference item |
| Published: |
Association for Uncertainty in Artificial Intelligence
2017
|