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06/08/2023
Autoencoding for the 'Good Dictionary' of eigen pairs of the Koopman Operator
Reduced order modelling relies on representing complex dynamical systems...
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08/01/2022
Learning Transfer Operators by Kernel Density Estimation
Inference of transfer operators from data is often formulated as a class...
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02/14/2022
Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling
Classical methods of solving spatiotemporal dynamical systems include st...
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09/22/2021
Randomized Projection Learning Method forDynamic Mode Decomposition
A data-driven analysis method known as dynamic mode decomposition (DMD) ...
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02/06/2020
On Geometry of Information Flow for Causal Inference
Causal inference is perhaps one of the most fundamental concepts in scie...
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04/10/2018
An information-theoretic, all-scales approach to comparing networks
As network research becomes more sophisticated, it is more common than e...
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11/02/2017
Geometric k-nearest neighbor estimation of entropy and mutual information
Like most nonparametric estimators of information functionals involving ...
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07/21/2017
A Nonlinear Dimensionality Reduction Framework Using Smooth Geodesics
Existing dimensionality reduction methods are adept at revealing hidden ...
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08/25/2016
Go With the Flow, on Jupiter and Snow. Coherence From Video Data without Trajectories
Viewing a data set such as the clouds of Jupiter, coherence is readily a...
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09/23/2015
Detecting phase transitions in collective behavior using manifold's curvature
If a given behavior of a multi-agent system restricts the phase variable...
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08/13/2015
Dimensionality Reduction of Collective Motion by Principal Manifolds
While the existence of low-dimensional embedding manifolds has been show...
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08/12/2015
