TR2020-169

Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks


    •  Anantharaman, R., Ma, Y., Gowda, S., Laughman, C.R., Shah, V., Edelman, A., Rackauckas, C., "Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks", Advances in Neural Information Processing Systems (NeurIPS), December 2020.
      BibTeX TR2020-169 PDF
      • @inproceedings{Anantharaman2020dec,
      • author = {Anantharaman, Ranjan and Ma, Yingbo and Gowda, Shashi and Laughman, Christopher R. and Shah, Viral and Edelman, Alan and Rackauckas, Chris},
      • title = {Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks},
      • booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
      • year = 2020,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2020-169}
      • }
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  • Research Areas:

    Machine Learning, Multi-Physical Modeling, Optimization

Abstract:

Modern design, control, and optimization often requires simulation of highly nonlinear models, leading to prohibitive computational costs. These costs can be amortized by evaluating a cheap surrogate of the full model. Here we present a general data-driven method, the continuous-time echo state network (CTESN), for generating surrogates of nonlinear ordinary differential equations with dynamics at widely separated timescales. We empirically demonstrate near-constant time performance using our CTESNs on a physically motivated scalable model of a heating system whose full execution time increases exponentially, while maintaining relative error of within 0.2 %. We also show that our model captures fast transients as well as slow dynamics effectively, while other techniques such as physics informed neural networks have difficulties trying to train and predict the highly nonlinear behavior of these models.

 

  • Related Publication

  •  Anantharaman, R., Ma, Y., Gowda, S., Laughman, C.R., Shah, V., Edelman, A., Rackauckas, C., "Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks", arXiv, December 2020.
    BibTeX
    • @article{Anantharaman2020dec2,
    • author = {Anantharaman, Ranjan and Ma, Yingbo and Gowda, Shashi and Laughman, Christopher R. and Shah, Viral and Edelman, Alan and Rackauckas, Chris},
    • title = {Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks},
    • journal = {arXiv},
    • year = 2020,
    • month = dec
    • }