Oscar Michel

Computer Vision and Pattern Recognition · 2021–2024

A researcher in the Science corpus: 4 papers; trusts 155 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Oscar Michel trusts overall

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

  1. Tero Karras
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Alec Radford
  8. Ross B. Girshick
  9. Yann LeCun
  10. Ilya Sutskever

Who trusts Oscar Michel overall

  1. Jiaxiang Tang
  2. Elad Richardson
  3. Gal Metzer
  4. Minghua Liu
  5. Rui Chen
  6. Lukas Höllein
  7. Omer Bar-Tal
  8. Haochen Wang
  9. Taoran Yi
  10. Yixun Liang

Papers from Oscar Michel's perspective

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

Their papers