Geoff Pleiss

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 8 papers; trusts 658 researchers and is trusted by 191 researchers here, as inferred from the citation graph.

Subfields

Whom Geoff Pleiss trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Yann LeCun
  6. Diederik P. Kingma
  7. Ilya Sutskever
  8. Ross B. Girshick
  9. Christian Szegedy
  10. X. Zhang

Who trusts Geoff Pleiss overall

  1. Pavel Izmailov
  2. Dan Hendrycks
  3. Andrew Gordon Wilson
  4. Wesley J. Maddox
  5. Ninareh Mehrabi
  6. Polina Kirichenko
  7. Mitchell Wortsman
  8. Aviral Kumar
  9. Jishnu Mukhoti
  10. Dana Pessach

Papers from Geoff Pleiss's perspective

Ordered by how strongly the researchers Geoff Pleiss 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. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers