Grace Zhang

Artificial Intelligence · with Levine · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 92 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Grace Zhang trusts overall

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

  1. Richard S. Sutton
  2. J. Urgen Schmidhuber
  3. Geoffrey E. Hinton
  4. Sergey Levine
  5. Diederik P. Kingma
  6. Jan Peters
  7. John Schulman
  8. Chelsea Finn
  9. Pieter Abbeel
  10. Yoshua Bengio

Who trusts Grace Zhang overall

  1. Sergey Levine
  2. Aviral Kumar
  3. Rafael Rafailov
  4. Tianhe Yu
  5. Ofir Nachum
  6. Ilya Kostrikov
  7. Xue Bin Peng
  8. Jorge Armando Mendez Mendez
  9. Ashvin Nair
  10. Chelsea Finn

Papers from Grace Zhang's perspective

Ordered by how strongly the researchers Grace Zhang 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. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. GENERATIVE ADVERSARIAL NETS
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers