John T. Hancock

Artificial Intelligence · 2020–2024

A researcher in the Science corpus: 3 papers; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John T. Hancock trusts overall

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

  1. Jerome H. Friedman
  2. Chih-Jen Lin
  3. Yoshua Bengio
  4. Sepp Hochreiter
  5. S. Kotsiantis
  6. Yoav Freund
  7. Geoffrey E. Hinton
  8. Tomas Mikolov
  9. Scott M. Lundberg
  10. Ilya Sutskever

Who trusts John T. Hancock overall

  1. Vadim Borisov
  2. Duncan C. McElfresh
  3. Tobias Leemann
  4. Sujay Khandagale

Papers from John T. Hancock's perspective

Ordered by how strongly the researchers John T. Hancock 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  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. ImageNet Large Scale Visual Recognition Challenge

Their papers