Pete Trautman

Computer Vision and Pattern Recognition · 2010–2021

A researcher in the Science corpus: 3 papers; trusts 58 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Pete Trautman trusts overall

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

  1. Sebastian Thrun
  2. Radford M. Neal
  3. Tom Minka
  4. Arnaud Doucet
  5. Steven M. LaValle
  6. Jonathan Ko
  7. Jur van den Berg
  8. Stefano Pellegrini
  9. M. Sanjeev Arulampalam
  10. Daphne Koller

Who trusts Pete Trautman overall

  1. Alexandre Alahi
  2. Christoforos Mavrogiannis
  3. Alexandre Robicquet
  4. Anirudh Vemula
  5. Changan Chen
  6. Rohan Chandra
  7. Fabian B. Fuchs
  8. Andrey Rudenko
  9. Yanjun Huang
  10. Francesca Baldini

Papers from Pete Trautman's perspective

Ordered by how strongly the researchers Pete Trautman 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. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers