Now showing items 13-15 of 74

    • Efficient Sampling Methods of, by, and for Stochastic Dynamical Systems 

      Zhang, Benjamin Jiahong (Massachusetts Institute of Technology, 2022-02)
      This thesis presents new methodologies that lie at the intersection of computational statistics and computational dynamics. Stochastic differential equations (SDEs) are used to model a variety of physical systems, and ...
    • An efficient algorithm for sensitivity analysis of chaotic systems 

      Chandramoorthy, Nisha (Massachusetts Institute of Technology, 2021-09)
      How does long-term chaotic behavior respond to small parameter perturbations? Using detailed models, chaotic systems are frequently simulated across disciplines – from climate science to astrophysics. But, an efficient ...
    • Applications of Deep Learning to Scientific Inverse Problems 

      Li, Matthew T. C. (Massachusetts Institute of Technology, 2021-09)
      The first part of this thesis introduces an end-to-end deep learning architecture, called the wide-band butterfly network (WideBNet), which comprehensively solves the inverse wave scattering problem across all length scales. ...