Methods for discovering causal knowledge from observational data have been a persistent topic of AI research for several decades. Essentially all of this work focuses on knowledge...
Marc Maier, Brian Taylor, Huseyin Oktay, David Jen...
Abstract--The development of accurate health condition prediction approaches has been a key research topic in condition based maintenance (CBM) in recent years. However, current he...
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into acco...
The Temporal Coding Hypothesis of Miller and colleagues [7] suggests that animals integrate related temporal patterns of stimuli into single memory representations. We formalize t...