A prediction rigidity formalism for low-cost uncertainties in trained neural networks

Filippo Bigi, Sanggyu Chong, Michele Ceriotti +1

Regression methods are fundamental for scientific and technological applications. However, fitted models can be highly unreliable outside of their training domain, and hence the qu…