Abstract: Accurate parametric identification of Linear Parameter-Varying (LPV ... Hence, it is attractive to estimate the underlying model structure of LPV systems based on measured data, i.e., to ...

The emergence of deep learning ... framework [Linear Graph Neural Network (LGNN)] with superior performance. The model first preprocesses the input graph, and uses symmetric normalization and feature ...

Abstract: In this paper, we analyze a Linear Quadratic (LQ) control problem in terms of the average cost and the structure of the value function. We develop a completely model-free reinforcement ...

Subsequently, Levy and Goldberg (2014) and Pennington et al (2014) tried to explain why such linear structure should arise in embeddings derived from nonlinear methods. We provide a new generative ...

uses machine learning to rapidly predict 3D protein structures that are so accurate they are indistinguishable from those experimentally derived by scientists. This open-source model has been used ...