activity
20172022
most citedUsing Machine Learning to Replicate Chaotic Attractors and Calculate Lyapunov Exponents from Data

633 citations · 1.1k across the 6 of their papers we have counts for

collaborators
Showing 2020Show all

2 papers · 1 filter

physics.comp-ph2020★ 20 cited

Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations

Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath +3

Simulation of turbulent flows at high Reynolds number is a computationally challenging task relevant to a large number of engineering and scientific applications in diverse fields…

cs.LG2020

Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems

Alexander Wikner, Jaideep Pathak, Brian Hunt +5

We consider the commonly encountered situation (e.g., in weather forecasting) where the goal is to predict the time evolution of a large, spatiotemporally chaotic dynamical system…