Michael Alexander Riegler

Computer Vision and Pattern Recognition · 2016–2022

A researcher in the Science corpus: 10 papers; trusts 173 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Alexander Riegler trusts overall

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

  1. Kaiming He
  2. Karen Simonyan
  3. Jorge Bernal
  4. Alex Krizhevsky
  5. Geoffrey E. Hinton
  6. Jia Deng
  7. Andrew Zisserman
  8. Christian Szegedy
  9. Liang-Chieh Chen
  10. Ilya Sutskever

Who trusts Michael Alexander Riegler overall

  1. Debesh Jha
  2. Qing Xu
  3. Bingzhi Chen
  4. Md Mostafijur Rahman
  5. Ailiang Lin
  6. Xiaoqi Zhao
  7. Taehun Kim
  8. Yundong Zhang
  9. Tao Zhou
  10. B. Dong

Papers from Michael Alexander Riegler's perspective

Ordered by how strongly the researchers Michael Alexander Riegler 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. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Going deeper with convolutions
  8. ImageNet: A large-scale hierarchical image database
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers