no code implementations • 28 Sep 2020 • Matthew Baucum, Anahita Khojandi, Theodore Papamarkou
To allow for this, we formulate a special case of recurrent neural networks (RNNs), which we name hidden Markov recurrent neural networks (HMRNNs), and prove that each HMRNN has the same likelihood function as a corresponding discrete-observation HMM.
no code implementations • 4 Jun 2020 • Matt Baucum, Anahita Khojandi, Theodore Papamarkou
Hidden Markov models (HMMs) are commonly used for disease progression modeling when the true patient health state is not fully known.
no code implementations • 4 Nov 2019 • Yiyang Wang, Neda Masoud, Anahita Khojandi
In this paper we propose a novel observer-based method to improve the safety and security of connected and automated vehicle (CAV) transportation.