Yadhu Kartha

Statistical and Nonlinear Physics · 2022

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yadhu Kartha trusts overall

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

  1. Maizar Raissi
  2. Lu Lu
  3. G. Em Karniadakis
  4. Sifan Wang
  5. Michael L. Stein
  6. Ilya M. Sobol
  7. Rémi Bardenet
  8. Melissa E. O'Neill

Papers from Yadhu Kartha's perspective

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

  1. fPINNs: Fractional Physics-Informed Neural Networks
  2. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  3. Physics-informed neural networks for inverse problems in nano-optics and metamaterials.
  4. DeepXDE: A Deep Learning Library for Solving Differential Equations
  5. GENERATIVE ADVERSARIAL NETS
  6. Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations
  7. Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
  8. Physics-informed neural networks for high-speed flows
  9. Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism (AAAI Spring Symposium: MLPS)
  10. Large sample properties of simulations using latin hypercube sampling

Their papers