Gabriel Goh

Artificial Intelligence · with Cotter · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 52 researchers here, as inferred from the citation graph.

Subfields

Whom Gabriel Goh trusts overall

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

  1. Keith Ball
  2. Shai Shalev-Shwartz
  3. Chih-Jen Lin
  4. Thorsten Joachims
  5. R. Tyrrell Rockafellar
  6. Mark A. Davenport
  7. Yurii E. Nesterov
  8. Tong Zhang
  9. Rong-En Fan
  10. Shun-ichi Amari

Who trusts Gabriel Goh overall

  1. James Lucas
  2. Andrew Cotter
  3. Jacob Jackson
  4. Heinrich Jiang
  5. Michael Ruogu Zhang
  6. Bernease Herman
  7. Atli Kosson
  8. Dana Pessach
  9. Guodong Zhang
  10. Lukas Ruff

Papers from Gabriel Goh's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers