William John Knottenbelt

Artificial Intelligence · 2014–2021

A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom William John Knottenbelt trusts overall

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

  1. Paul J. Werbos
  2. Alex Graves
  3. Geoffrey E. Hinton
  4. Ilya Sutskever
  5. Ronald J. Williams
  6. Alex Krizhevsky
  7. Yoshua Bengio
  8. David E. Rumelhart
  9. Jack Kelly
  10. Yann LeCun

Who trusts William John Knottenbelt overall

  1. Jack Kelly
  2. Chaoyun Zhang

Papers from William John Knottenbelt's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers