Gail Weiss

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Gail Weiss trusts overall

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

  1. Jeffrey L. Elman
  2. Kyunghyun Cho
  3. Yoshua Bengio
  4. Geoffrey E. Hinton
  5. C. Lee Giles
  6. Junyoung Chung
  7. Dana Angluin
  8. Henrik Jacobsson
  9. Quoc V. Le
  10. J. Urgen Schmidhuber

Who trusts Gail Weiss overall

  1. Jean-Philippe Bernardy
  2. Sebastian Ruder
  3. Shaked Brody
  4. Anurag Koul
  5. Eric Wallace
  6. Yonatan Belinkov
  7. Michael R Douglas
  8. Michael Hahn
  9. Ivan Vulic
  10. Uri Alon

Papers from Gail Weiss's perspective

Ordered by how strongly the researchers Gail Weiss 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. Long Short-Term Memory
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers