49 citations · 271 across the 22 of their papers we have counts for
5 papers · 1 filter
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points
Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui +4
We present a machine learning (ML)-assisted framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale modeling, for (a) detecting tipp…
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning
Dimitrios G. Patsatzis, Gianluca Fabiani, Lucia Russo +1
We present a physics-informed machine-learning (PIML) approach for the approximation of slow invariant manifolds (SIMs) of singularly perturbed systems, providing functionals in an…
Tipping points in overturning circulation mediated by ocean mixing and the configuration and magnitude of the hydrological cycle: A simple model
Anand Gnanadesikan, Gianluca Fabiani, Jingwen Liu +7
The current configuration of the ocean overturning involves upwelling predominantly in the Southern Ocean and sinking predominantly in the Atlantic basin. The reasons for this rema…
On the accuracy of interpolation based on single-layer artificial neural networks with a focus on defeating the Runge phenomenon
Ferdinando Auricchio, Maria Roberta Belardo, Gianluca Fabiani +2
In the present paper, we consider one-hidden layer ANNs with a feedforward architecture, also referred to as shallow or two-layer networks, so that the structure is determined by t…
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning
Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis +2
We present a physics-informed machine learning (PIML) scheme for the feedback linearization of nonlinear discrete-time dynamical systems. The PIML finds the nonlinear transformatio…