Gaussian-Dirichlet Random Fields for Inference over High Dimensional Categorical Observations
JE San Soucie, HM Sosik… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
We propose a generative model for the spatio-temporal distribution of high dimensional
categorical observations. These are commonly produced by robots equipped with an …
categorical observations. These are commonly produced by robots equipped with an …
[PDF][PDF] Continuous hourly observations of chlorophyll fluorescence
CS Roesler - 2022 - mwra.com
Since late 2000, MWRA has discharged treated wastewater from its Deer Island Treatment
Plant in Boston through a 15 km (9 mi) tunnel into Massachusetts Bay. To help ensure that …
Plant in Boston through a 15 km (9 mi) tunnel into Massachusetts Bay. To help ensure that …
[图书][B] Unsupervised learning of interpretable models for sparse, smooth data
A Kalmbach - 2019 - search.proquest.com
This thesis considers learning unsupervised representations that facilitate understanding
how complex data varies over space and time–in other words learning interpretable …
how complex data varies over space and time–in other words learning interpretable …