A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
Identifying the historical data that is the best analog with a pattern from which a forecast is sought allows time series data to be extrapolated. That technique of best analogs i...
Abstract. Measurement and modelling of distributions of data communication times is commonly done for telecommunication networks, but this has not previously been done for message ...
: The Time-Triggered (TT) model of computation is a model for the representation and analysis of the design of large hard real-time systems. Central to this model is the concept of...
Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...
Chris Bailey-Kellogg, Sheetal Chainraj, Gopal Pand...