We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis ...
Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Tod...
Since perceptual and motor processes in the brain are the result of interactions between neurons, layers and areas, a lot of attention has been directed towards the development of...
In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Many sensor network applications monitor continuous phenomena by sampling, and fit time-varying models that capture the phenomena's behaviors. We introduce Pulse, a framework...