Peter Jung

Artificial Intelligence · 2014–2021

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Jung trusts overall

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

  1. Radford M. Neal
  2. Geoffrey E. Hinton
  3. David John Cameron MacKay
  4. Yann LeCun

Who trusts Peter Jung overall

  1. Frank Schaich

Papers from Peter Jung's perspective

Ordered by how strongly the researchers Peter Jung 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. Gradient-based learning applied to document recognition
  4. Distilling the Knowledge in a Neural Network (arXiv.org)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Learning Multiple Layers of Features from Tiny Images
  7. ImageNet: A large-scale hierarchical image database
  8. Rethinking the Inception Architecture for Computer Vision
  9. Long Short-Term Memory
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers