Frederik Fuest

Computational Mechanics · 2012–2021

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

Subfields

Whom Frederik Fuest trusts overall

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

  1. Markus Raffel

Papers from Frederik Fuest's perspective

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

  1. Automatic differentiation in machine learning: a survey
  2. Particle Image Velocimetry: A Practical Guide
  3. Solving high-dimensional partial differential equations using deep learning
  4. Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
  5. Turbulence Modeling in the Age of Data (Annual Review of Fluid Mechanics)
  6. Machine Learning for Fluid Mechanics (Annual Review of Fluid Mechanics)
  7. B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
  8. Planar laser induced fluorescence in aqueous flows
  9. Background-oriented schlieren (BOS) techniques
  10. Density measurements using the Background Oriented Schlieren technique

Their papers