Robert M. Kirby

Statistical and Nonlinear Physics · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Robert M. Kirby trusts

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

  1. Paris Perdikaris (in Statistical and Nonlinear Physics)
  2. G. Em Karniadakis (in Statistical and Nonlinear Physics)

Papers from Robert M. Kirby's perspective

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

  1. Et al
  2. Curriculum learning
  3. Artificial neural networks for solving ordinary and partial differential equations
  4. Solving high-dimensional partial differential equations using deep learning
  5. Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations
  6. DGM: A deep learning algorithm for solving partial differential equations
  7. DeepXDE: A Deep Learning Library for Solving Differential Equations
  8. Understanding and mitigating gradient pathologies in physics-informed neural networks
  9. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  10. Physics-informed neural networks for inverse problems in nano-optics and metamaterials.

Their papers