Gege Wen

Statistical and Nonlinear Physics · 2021

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

Subfields

Whom Gege Wen trusts overall

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

  1. Zong-Yi Li
  2. Yinhao Zhu
  3. Maizar Raissi
  4. Paris Perdikaris
  5. Nikola B. Kovachki
  6. Nicholas Zabaras
  7. Alexandre Boucher
  8. G. Em Karniadakis

Who trusts Gege Wen overall

  1. Zong-Yi Li
  2. Haixu Wu
  3. Daniel Zhengyu Huang

Papers from Gege Wen's perspective

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

  1. Fourier Neural Operator for Parametric Partial Differential Equations (International Conference on Learning Representations)
  2. Neural Operator: Graph Kernel Network for Partial Differential Equations (International Conference on Learning Representations)
  3. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
  4. Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data
  5. Applied Geostatistics with SGeMS: A User's Guide
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Multipole Graph Neural Operator for Parametric Partial Differential Equations (Neural Information Processing Systems)
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. ImageNet classification with deep convolutional neural networks
  10. Multilayer feedforward networks are universal approximators

Their papers