20 citations · 37 across the 13 of their papers we have counts for
5 papers · 1 filter
A Constructive Approach for One-Shot Training of Neural Networks Using Hypercube-Based Topological Coverings
W. Brent Daniel, Enoch Yeung
In this paper we presented a novel constructive approach for training deep neural networks using geometric approaches. We show that a topological covering can be used to define a c…
Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks
Panos Stinis, Tobias Hagge, Alexandre M. Tartakovsky +1
We suggest ways to enforce given constraints in the output of a Generative Adversarial Network (GAN) generator both for interpolation and extrapolation (prediction). For the case o…
A Class of Logistic Functions for Approximating State-Inclusive Koopman Operators
Charles A. Johnson, Enoch Yeung
An outstanding challenge in nonlinear systems theory is identification or learning of a given nonlinear system's Koopman operator directly from data or models. Advances in extended…
Solving differential equations with unknown constitutive relations as recurrent neural networks
Tobias Hagge, Panos Stinis, Enoch Yeung +1
We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variable…
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems
Enoch Yeung, Soumya Kundu, Nathan Hodas
The Koopman operator has recently garnered much attention for its value in dynamical systems analysis and data-driven model discovery. However, its application has been hindered by…