Michael Hind

Artificial Intelligence · 2000–2019

A researcher in the Science corpus: 9 papers; trusts 2 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Hind trusts overall

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

  1. Stephen Chong
  2. Solon Barocas
  3. Kush R. Varshney
  4. Omar Zaidan
  5. Andrew D. Selbst
  6. Niklas Möller
  7. Geoffrey E. Hinton
  8. Sandra Wachter
  9. Finale Doshi-Velez
  10. Cynthia Rudin

Who trusts Michael Hind overall

  1. Chris Lattner
  2. Mahima Pushkarna
  3. Philipp Schmidt
  4. Gogul Balakrishnan
  5. Vijay Victor D'Silva
  6. Bo Li
  7. Maryam Ashoori
  8. Enes Göktas
  9. Silverio Martínez-Fernández
  10. Umang Bhatt

Papers from Michael Hind's perspective

Ordered by how strongly the researchers Michael Hind 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. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Distilling the Knowledge in a Neural Network (arXiv.org)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Learning Multiple Layers of Features from Tiny Images

Their papers