The reason being, the model may not be able to perform well even on existing training data since the lower degree polynomials are unable to capture all features of the training data. Yet the variance ...

Bias is the difference between the average prediction of a model and the correct value which we are trying to predict. Model with high bias means very little attention is given to the training data ...

Inter-individual differences in a local measure of brain structure — for example, cortical thickness — often co-vary with inter-individual differences in the structure of other brain regions.

Abstract: Stochastic graph neural networks (SGNNs) are information processing architectures that learn representations from data over random graphs. SGNNs are trained with respect to the expected ...