Sili Deng

Statistical and Nonlinear Physics · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Sili Deng trusts overall

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

  1. Maizar Raissi

Papers from Sili Deng's perspective

Ordered by how strongly the researchers Sili Deng trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Understanding the difficulty of training deep feedforward neural networks
  2. DeepXDE: A Deep Learning Library for Solving Differential Equations
  3. Variational Physics-Informed Neural Networks For Solving Partial Differential Equations
  4. Artificial neural networks for solving ordinary and partial differential equations
  5. Understanding and mitigating gradient pathologies in physics-informed neural networks
  6. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  7. Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations
  8. PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs
  9. Data Driven Governing Equations Approximation Using Deep Neural Networks (Journal of Computational Physics)
  10. Learning data-driven discretizations for partial differential equations (Proceedings of the National Academy of Sciences of the United States of America)

Their papers