Miguel Liu-Schiaffini

Statistical and Nonlinear Physics · 2023

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Miguel Liu-Schiaffini trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Andrew M. Stuart
  2. Zong-Yi Li

Papers from Miguel Liu-Schiaffini's perspective

Ordered by how strongly the researchers Miguel Liu-Schiaffini trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Fourier Neural Operator for Parametric Partial Differential Equations (International Conference on Learning Representations)
  2. Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators (Nature Machine Intelligence)
  3. Error estimates for DeepOnets: A deep learning framework in infinite dimensions (Transactions of Mathematics and Its Applications)
  4. Inverse problems: A Bayesian perspective (Acta Numerica)
  5. Learning the solution operator of parametric partial differential equations with physics-informed DeepONets (Science Advances)
  6. Solving high-dimensional partial differential equations using deep learning
  7. Introduction to the finite element method (Finite Element Analysis)
  8. Physics-Informed Neural Operator for Learning Partial Differential Equations (ACM / IMS Journal of Data Science)
  9. Spectral Methods in MATLAB
  10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers