The inductive biases of trained neural networks are difficult to understand and,
consequently, to adapt to new settings. We study the inductive biases of linearizations of …

This article presents a novel approach to construct Intrinsic Gaussian Processes for
regression on unknown manifolds with probabilistic metrics (GPUM) in point clouds. In many …

We propose to linearize neural networks for transfer learning via a first order Taylor
approximation. Making neural networks linear in this way allows the optimization to become …