Tom Bagby

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 6 papers; trusts 58 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Tom Bagby trusts overall

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

  1. Alex Graves
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Diederik P. Kingma
  5. J. Urgen Schmidhuber
  6. Hasim Sak
  7. Daniel Povey
  8. Kaiming He
  9. Abdel-rahman Mohamed
  10. Alex Krizhevsky

Who trusts Tom Bagby overall

  1. Khe Chai Sim
  2. Gakuto Kurata
  3. Franccoise Beaufays
  4. George Saon
  5. Jinyu Li
  6. Chung-Cheng Chiu
  7. Petr Zadrazil
  8. Ehsan Variani

Papers from Tom Bagby's perspective

Ordered by how strongly the researchers Tom Bagby 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. Long Short-Term Memory
  3. ImageNet classification with deep convolutional neural networks
  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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  8. ImageNet: A large-scale hierarchical image database
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers