activity
20172020
most citedProbabilistic response and rare events in Mathieu's equation under correlated parametric excitation

34 citations · 38 across the 7 of their papers we have counts for

collaborators

10 papers

math.NA2020

A Local Spectral Exterior Calculus for the Sphere and Application to the Shallow Water Equations

Clauson Carvalho da Silva, Christian Lessig, Boyko Dodov +2

We introduce , a local spectral exterior calculus for the two-sphere . provides a discretization of Cartan's exterior calculus on formed by…

physics.flu-dyn2019

A Gaussian moment method and its augmentation via LSTM recurrent neural networks for the statistics of cavitating bubble populations

Spencer H. Bryngelson, Alexis Charalampopoulos, Themistoklis P. Sapsis +1

Phase-averaged dilute bubbly flow models require high-order statistical moments of the bubble population. The method of classes, which directly evolve bins of bubbles in the probab…

physics.flu-dyn20191 cited

Bubbles in Turbulent Flows: Data-driven, kinematic models with memory terms

Zhong Yi Wan, Petr Karnakov, Petros Koumoutsakos +1

We present data driven kinematic models for the motion of bubbles in high-Re turbulent fluid flows based on recurrent neural networks with long-short term memory enhancements. The…

eess.SP2019

Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics

Pantelis R. Vlachas, Jaideep Pathak, Brian R. Hunt +4

We examine the efficiency of Recurrent Neural Networks in forecasting the spatiotemporal dynamics of high dimensional and reduced order complex systems using Reservoir Computing (R…

math.DS20193 cited

Machine-Learning Ocean Dynamics from Lagrangian Drifter Trajectories

Nikolas O. Aksamit, Themistoklis P. Sapsis, George Haller

Lagrangian ocean drifters provide highly accurate approximations of ocean surface currents but are sparsely located across the globe. As drifters passively follow ocean currents, t…

physics.comp-ph2019

Learning the Tangent Space of Dynamical Instabilities from Data

Antoine Blanchard, Themistoklis P. Sapsis

For a large class of dynamical systems, the optimally time-dependent (OTD) modes, a set of deformable orthonormal tangent vectors that track directions of instabilities along any t…