The driven double-well Duffing oscillator is a well-studied system that manifests a wide variety of dynamics, from periodic behavior to chaos, and describes a diverse array of physical systems. It has been shown to be relevant in understanding chaos in the classical to quantum transition. Here we explore the complexity of its dynamics in the classical and semi-classical regimes, using the techn...

Ordinal embedding aims at finding a low dimensional representation of objects from set constraints the form ”item j is closer to item i than k”. Typically, each object mapped onto point vector in metric space. We argue that mapping density instead provides some interesting advantages, including an inherent reflection uncertainty about itself and its relative location Indeed, this paper, we prop...

The most widely studied problem in machine learning is supervised learning. We are given a labeled training set of input-output pairs, D = (xi, yi)i=1, and have to learn a way to predict the output or target ỹ for a novel test input x̃ (i.e, for x̃ 6∈ D). (We use the tilde notation to denote test cases that we have not seen before.) Some examples include: predicting if someone has cancer ỹ ∈ {0, ...