Julien Philip

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 2 papers; trusts 111 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Julien Philip trusts overall

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

  1. Yasutaka Furukawa
  2. Diederik P. Kingma
  3. Johannes L. Schönberger
  4. Geoffrey E. Hinton
  5. Kaiming He
  6. Alex Krizhevsky
  7. Yoshua Bengio
  8. Yann LeCun
  9. Ross B. Girshick
  10. David G. Lowe

Who trusts Julien Philip overall

  1. Peter Hedman
  2. Ben Mildenhall
  3. Jonathan T. Barron
  4. Pratul P. Srinivasan
  5. Richard Tucker
  6. J. Lee
  7. Antoine Guédon
  8. Gernot Riegler
  9. Justus Thies
  10. Simon Niedermayr

Papers from Julien Philip's perspective

Ordered by how strongly the researchers Julien Philip 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. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Gradient-based learning applied to document recognition
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Long Short-Term Memory
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers