Tom Wehrbein

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tom Wehrbein trusts overall

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

  1. Diederik P. Kingma
  2. Paul Bergmann
  3. Jimmy Ba

Papers from Tom Wehrbein's perspective

Ordered by how strongly the researchers Tom Wehrbein trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Learning Multiple Layers of Features from Tiny Images
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. ImageNet Large Scale Visual Recognition Challenge
  9. GENERATIVE ADVERSARIAL NETS
  10. ImageNet: A large-scale hierarchical image database

Their papers