Keith D. Humfeld

Statistical and Nonlinear Physics · 2001–2020

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Keith D. Humfeld trusts overall

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

  1. Maizar Raissi
  2. Justin A. Sirignano
  3. Nicholas Wagner
  4. Jian-Xun Wang
  5. Anand Pratap Singh
  6. Jiequn Han
  7. Paris Perdikaris
  8. Konstantinos Spiliopoulos
  9. G. Em Karniadakis
  10. James M. Rondinelli

Who trusts Keith D. Humfeld overall

  1. S. Niaki

Papers from Keith D. Humfeld's perspective

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

  1. Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data
  2. DGM: A deep learning algorithm for solving partial differential equations
  3. Solving high-dimensional partial differential equations using deep learning
  4. Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  5. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  6. Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Theory-Guided Machine Learning in Materials Science
  9. Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science
  10. Photonic Crystals

Their papers