Paul K. Rubenstein

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 8 papers; trusts 67 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Paul K. Rubenstein trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Michael I. Jordan
  4. Yoshua Bengio
  5. Aapo Hyvärinen
  6. Alex Krizhevsky
  7. Yann LeCun
  8. Radford M. Neal
  9. Bernhard Schölkopf
  10. Kaiming He

Who trusts Paul K. Rubenstein overall

  1. Bernhard Schölkopf
  2. Francesco Locatello
  3. Stefan Bauer
  4. Xiaohua Zhai
  5. Stephan Bongers
  6. Atticus Geiger
  7. Jan Peters
  8. Niklas Pfister
  9. Joan Puigcerver
  10. Michael Tschannen

Papers from Paul K. Rubenstein's perspective

Ordered by how strongly the researchers Paul K. Rubenstein 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. GENERATIVE ADVERSARIAL NETS

Their papers