This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

Abstract: The recursive Gaussian process regression (RGPR ... Most of existing RGPR models are on the assumption that hyperparameters in the covariance function are fixed during the model calibration.

Binary logistic regression is a very popular predictive model that is widely used in various fields. In binary logistic regression, data is first analyzed, then the probability of individual events is ...