This repository houses a set of functions dedicated to the study of how well neural networks can learn a piecewise function dataset of varying complexity. You will find code dedicated to generating ...

In this paper, we propose a method for finding the best piecewise linearization of nonlinear functions. For this aim, we try to obtain the best approximation of a nonlinear function as a piecewise ...

A python implementation of the algorithm used to generate optimal piecewise linear approximations of convex functions proposed by Imamoto and Tang [1]. The algorithm uses an iterative search to find ...

Abstract: Inspired by the idea of multiple Lyapunov functions (MLFs), we use piecewise continuous scalar functions to investigate the stabilizability of time-varying switched systems. Starting with ...

Humans are capable of learning a new fine-grained concept with very little supervision, e.g., few exemplary images for a species of bird, yet our best deep learning systems need hundreds or thousands ...

Dose-response meta-analysis (DRMA) is widely employed to establishing the potential dose-response relationship between continuous exposures and disease outcomes. However, no method is readily ...