260 citations · 412 across the 12 of their papers we have counts for
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cs.AI2013★ 5 cited
Learning Hidden Markov Models with Geometrical Constraints
Hagit Shatkay
Hidden Markov models (HMMs) and partially observable Markov decision processes (POMDPs) form a useful tool for modeling dynamical systems. They are particularly useful for represen…
cs.AI2011★ 27 cited
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
L. P. Kaelbling, H. Shatkay
Hidden Markov models (HMMs) and partially observable Markov decision processes (POMDPs) provide useful tools for modeling dynamical systems. They are particularly useful for repres…