103 citations · 682 across the 48 of their papers we have counts for
3 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…
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…
Coarse-scale PDEs from fine-scale observations via machine learning
Seungjoon Lee, Mahdi Kooshkbaghi, Konstantinos Spiliotis +2
Complex spatiotemporal dynamics of physicochemical processes are often modeled at a microscopic level (through e.g. atomistic, agent-based or lattice models) based on first princip…