March

Reinforcement Learning · with Bagnell · 2015

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom March trusts overall

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

  1. Stéphane Ross
  2. Brian D. Ziebart
  3. J. Bagnell
  4. Andrew Y. Ng
  5. Nathan D. Ratliff
  6. Pieter Abbeel
  7. Yoshua Bengio
  8. Daniel Munoz
  9. Geoffrey E. Hinton
  10. Yann LeCun

Who trusts March overall

  1. Brandon Packard
  2. Devendra Singh Chaplot
  3. Takayuki Osa
  4. Santiago Ontañón

Papers from March's perspective

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

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

Their papers