Linda Petzold

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Linda Petzold trusts overall

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

  1. Maizar Raissi

Papers from Linda Petzold's perspective

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

  1. Automatic differentiation in machine learning: a survey
  2. Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
  3. Neural Ordinary Differential Equations
  4. Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
  5. Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations
  6. Inferring solutions of differential equations using noisy multi-fidelity data
  7. Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations
  8. Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational models
  9. Machine learning of linear differential equations using Gaussian processes
  10. Learning Parameters and Constitutive Relationships with Physics Informed Deep Neural Networks

Their papers