Eric Heiden

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Eric Heiden trusts overall

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

  1. Diederik P. Kingma
  2. Igor Mordatch
  3. Andrew L. Maas
  4. Zijun Zhang
  5. Peter K. Allen

Papers from Eric Heiden's perspective

Ordered by how strongly the researchers Eric Heiden 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. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
  5. Histograms of oriented gradients for human detection
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Long Short-Term Memory
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers