Hong Ge

Probabilistic & Bayesian Methods · 2018

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hong Ge trusts overall

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

  1. Tom Minka
  2. Zoubin Ghahramani
  3. John M. Winn
  4. Matthew D. Hoffman
  5. Avi Pfeffer
  6. David J. Lunn
  7. Lawrence M. Murray
  8. Radford M. Neal
  9. Charles M. Bishop
  10. Andrew Gelman

Who trusts Hong Ge overall

  1. Vikash K. Mansinghka
  2. Marco F. Cusumano-Towner
  3. Feras A. Saad
  4. Ulrich Schaechtle
  5. Gwonsoo Che

Papers from Hong Ge's perspective

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

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

Their papers