Christian Weilbach

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Christian Weilbach trusts overall

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

  1. Diederik P. Kingma
  2. Jonathan Ho
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Alex Krizhevsky
  6. Kaiming He

Papers from Christian Weilbach's perspective

Ordered by how strongly the researchers Christian Weilbach 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. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  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