activity
20182022
most citedLearning Koopman Representations for Hybrid Systems

5 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SY2022

Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem

Ethan King, Jan Drgona, Aaron Tuor +4

The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a powe…

math.DS20205 cited

Learning Koopman Representations for Hybrid Systems

Craig Bakker, Arnab Bhattacharya, Samrat Chatterjee +2

The Koopman operator lifts nonlinear dynamical systems into a functional space of observables, where the dynamics are linear. In this paper, we provide three different Koopman repr…

math.DS20201 cited

Learning Bounded Koopman Observables: Results on Stability, Continuity, and Controllability

Craig Bakker, Thiagarajan Ramachandran, W. Steven Rosenthal

The Koopman operator is an useful analytical tool for studying dynamical systems -- both controlled and uncontrolled. For example, Koopman eigenfunctions can provide non-local stab…

math.DS2019

Koopman Representations of Dynamic Systems with Control

Craig Bakker, Steven Rosenthal, Kathleen E. Nowak

The design and analysis of optimal control policies for dynamical systems can be complicated by nonlinear dependence in the state variables. Koopman operators have been used to sim…

cs.LG2018

The Outer Product Structure of Neural Network Derivatives

Craig Bakker, Michael J. Henry, Nathan O. Hodas

In this paper, we show that feedforward and recurrent neural networks exhibit an outer product derivative structure but that convolutional neural networks do not. This structure ma…