Gang Bao

Statistical and Nonlinear Physics · with Ye · 2019

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Gang Bao trusts overall

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

  1. Maizar Raissi
  2. Paris Perdikaris
  3. Randall J. LeVeque
  4. Justin A. Sirignano
  5. Yibo Yang
  6. E. Weinan
  7. Jens Berg
  8. Mohammad Amin Nabian
  9. John C. Duchi
  10. Isaac E. Lagaris

Papers from Gang Bao's perspective

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

  1. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Long Short-Term Memory
  4. Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. ImageNet classification with deep convolutional neural networks
  7. Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations
  8. Artificial neural networks for solving ordinary and partial differential equations
  9. A unified deep artificial neural network approach to partial differential equations in complex geometries
  10. Gradient-based learning applied to document recognition

Their papers