We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
In this position paper, we present MEADOWS, a software framework that we are building at HKUST (The Hong Kong University of Science and Technology) for modeling, emulation, and an...
Qiong Luo, Lionel M. Ni, Bingsheng He, Hejun Wu, W...
The development of user interfaces based on vision and speech requires the solution of a challenging statistical inference problem: The intentions and actions of multiple individu...
Security for Next Generation Networks (NGNs) is an attractive topic for many research groups. The Y-Comm security group believes that a new security approach is needed to address t...
Glenford E. Mapp, Mahdi Aiash, Aboubaker Lasebae, ...