Vector time series data are widely met in practice. In this paper we propose a multivariate functional-coefficient regression model with heteroscedasticity for modelling such data. A local linear ...

We introduce continuously additive models, which can be viewed as extensions of additive regression models with vector predictors to the case of infinite-dimensional predictors. This approach produces ...

Apply Nonlinear Support Vector Machines (NSVMs) and Fourier transforms to analyze and process visual data. Use probabilistic reasoning and implement Recurrent Neural Networks (RNNs) to model temporal ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...