2017

  1. Parametric Gaussian Process Regression for Big Data Raissi, Maziar arXiv preprint arXiv:1704.03144 2017 [URL]
  2. Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations Raissi, Maziar, and Karniadakis, George Em arXiv preprint arXiv:1708.00588 2017 [URL]
  3. Inferring solutions of differential equations using noisy multi-fidelity data Raissi, Maziar, Perdikaris, Paris, and Karniadakis, George Em Journal of Computational Physics 2017 [URL]
  4. Machine learning of linear differential equations using gaussian processes Raissi, Maziar, Perdikaris, Paris, and Karniadakis, George Em Journal of Computational Physics 2017 [URL]
  5. Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations Raissi, Maziar, Perdikaris, Paris, and Karniadakis, George Em arXiv preprint arXiv:1703.10230 2017 [URL]
  6. Application of local improvements to reduced-order models to sampling methods for nonlinear PDEs with noise Raissi, M., and Seshaiyer, P. International Journal of Computer Mathematics 2017 [URL]
  7. Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling Perdikaris, P., Raissi, M., Damianou, A., Lawrence, N. D., and Karniadakis, G. E. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 2017 [URL]

2016

  1. Conic economics Raissi, Maziar 2016 [URL]
  2. Deep Multi-fidelity Gaussian Processes Raissi, Maziar, and Karniadakis, George arXiv preprint arXiv:1604.07484 2016 [URL]

2014

  1. The differential effects of oil demand and supply shocks on the global economy Cashin, Paul, Mohaddes, Kamiar, Raissi, Maziar, Raissi, Mehdi Energy Economics 2014 [URL]
  2. A multi-fidelity stochastic collocation method for parabolic partial differential equations with random input data Raissi, Maziar, and Seshaiyer, Padmanabhan International Journal for Uncertainty Quantification 2014 [URL]

2013

  1. Multi-fidelity Stochastic Collocation Raissi, Maziar 2013 [URL]