Publications

For a complete list of the group's publications please refer to our Google Scholar page. Selected preprints and journal papers are listed below. 

 

Preprints

  1. Angran Li, Stephen Becker, Alireza Doostan, Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction;
  2. Grant Norman, Jacqueline Wentz, Hemanth Kolla, Kurt Maute, Alireza Doostan, Constrained or Unconstrained? Neural-Network-Based Equation Discovery from Data;
  3. Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan, Fast algorithms for monotone lower subsets of Kronecker least squares problems;
  4. Alec Michael Dunton, Alireza Doostan, Deterministic matrix sketches for low-rank compression of high-dimensional simulation data;

Selected Journals

  1. Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan, QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression, Journal of Computational Physics (498), 2024.
  2. Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan, Subsampling of parametric models with bifidelity boosting, SIAM/ASA Journal on Uncertainty Quantification, 2024.
  3. Nuojin Cheng, Osman Asif Malik, Subhayan De, Stephen Becker, Alireza Doostan, Bi-fidelity variational auto-encoder for uncertainty quantification, Computer Methods in Applied Mechanics and Engineering, 2024.
  4. Jeffrey M Hokanson, Gianluca Iaccarino, Alireza Doostan, Simultaneous identification and denoising of dynamical systems, SIAM Journal on Scientific Computing, 2023.
  5. Jacqueline Wentz, Alireza Doostan, Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data, Computer Methods in Applied Mechanics and Engineering, 2023.
  6. Alexandre Cortiella, Kwang-Chun Park, Alireza Doostan, A priori denoising strategies for sparse identification of nonlinear dynamical systems: A comparative study, Journal of Computing and Information Science in Engineering, 2023.
  7. Jacqueline Wentz, Alireza Doostan, GenMod: A generative modeling approach for spectral representation of PDEs with random inputs, Journal of Computational Physics, 2023.
  8. Subhayan De, Kurt Maute, Alireza Doostan, Topology optimization under microscale uncertainty using stochastic gradients, Structural and Multidisciplinary Optimization, 2023.
  9. Subhayan De, Alireza Doostan, Neural network training using ℓ1-regularization and bi-fidelity data, Journal of Computational Physics, 2022.
  10. Subhayan De, Bhuiyan Shameem Mahmood Ebna Hai, Alireza Doostan, Markus Bause, Prediction of Ultrasonic Guided Wave Propagation in Fluid–Structure and Their Interface under Uncertainty Using Machine Learning, Journal of Engineering Mechanics, 2022.