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Bridging the Gap: Machine Learning to Resolve Improperly Modeled
  Dynamics

Bridging the Gap: Machine Learning to Resolve Improperly Modeled Dynamics

23 August 2020
Maan Qraitem
D. Kularatne
Eric Forgoston
M. A. Hsieh
    AI4CE
ArXivPDFHTML

Papers citing "Bridging the Gap: Machine Learning to Resolve Improperly Modeled Dynamics"

4 / 4 papers shown
Title
Leveraging Predictive Models for Adaptive Sampling of Spatiotemporal
  Fluid Processes
Leveraging Predictive Models for Adaptive Sampling of Spatiotemporal Fluid Processes
Sandeep Manjanna
Tom Z. Jiahao
M. A. Hsieh
18
0
0
03 Apr 2023
RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed
  Neural Network
RAMP-Net: A Robust Adaptive MPC for Quadrotors via Physics-informed Neural Network
Sourav Sanyal
Kaushik Roy
PINN
42
22
0
19 Sep 2022
KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework
  for Aerial Robots
KNODE-MPC: A Knowledge-based Data-driven Predictive Control Framework for Aerial Robots
K. Y. Chee
Tom Z. Jiahao
M. A. Hsieh
27
63
0
10 Sep 2021
Knowledge-Based Learning of Nonlinear Dynamics and Chaos
Knowledge-Based Learning of Nonlinear Dynamics and Chaos
Tom Z. Jiahao
M. Hsieh
Eric Forgoston
13
31
0
07 Oct 2020
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