Hong Jun Jeon

Reinforcement Learning · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 41 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Hong Jun Jeon trusts overall

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

  1. Diederik P. Kingma
  2. Sergey Levine
  3. Carl Doersch
  4. Andrew Y. Ng
  5. Geoffrey E. Hinton
  6. Pieter Abbeel
  7. Anca Dragan
  8. Jonathan Ho
  9. Chelsea Finn
  10. Yoshua Bengio

Who trusts Hong Jun Jeon overall

  1. Siddharth Karamcheti
  2. Jessy Lin
  3. Megha Srivastava
  4. Dorsa Sadigh
  5. Stephen Casper
  6. Daniel Fried
  7. A. Zhai
  8. Percy Liang
  9. Dylan P. Losey
  10. Anca Dragan

Papers from Hong Jun Jeon's perspective

Ordered by how strongly the researchers Hong Jun Jeon 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers