Learning Seasonal Phytoplankton Communities with Topic Models [2nd prize in the student poster competition at the OCEANS17]
We have developed a probabilistic generative model for phytoplankton communities. The proposed model takes counts of a set of phytoplankton taxa in a timeseries as its training data, and models communities by learning sparse co-occurrence structure between the taxa. Our model is probabilistic, where communities are represented by probability distributions