Scott Fujimoto

Reinforcement Learning · 2018–2022

A researcher in the Science corpus: 7 papers; trusts 468 researchers and is trusted by 672 researchers here, as inferred from the citation graph.

Subfields

Whom Scott Fujimoto trusts overall

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

  1. Richard S. Sutton
  2. Diederik P. Kingma
  3. Geoffrey E. Hinton
  4. Sergey Levine
  5. John Schulman
  6. Alex Krizhevsky
  7. Yoshua Bengio
  8. Sham M. Kakade
  9. E. Todorov
  10. Martin A. Riedmiller

Who trusts Scott Fujimoto overall

  1. Sergey Levine
  2. Aviral Kumar
  3. Ilya Kostrikov
  4. Ofir Nachum
  5. Shixiang Shane Gu
  6. Pieter Abbeel
  7. Justin Fu
  8. Caglar Gulcehre
  9. Ashvin Nair
  10. Robert Dadashi

Papers from Scott Fujimoto's perspective

Ordered by how strongly the researchers Scott Fujimoto 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. GENERATIVE ADVERSARIAL NETS

Their papers