—This paper details a learning decision-theoretic intelligent agent designed to solve the problem of guiding vehicles in the context of Personal Rapid Transit (PRT). The intellig...
We address the problem of pronunciation variation in conversational speech with a context-dependent articulatory featurebased model. The model is an extension of previous work usi...
Preethi Jyothi, Karen Livescu, Eric Fosler-Lussier
A Skilligent robot must be able to learn skills autonomously to accomplish a task. "Skilligence" is the capacity of the robot to control behaviors reasonably, based on th...
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...