Mike Kestemont

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Mike Kestemont trusts overall

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

  1. Sepp Hochreiter
  2. Yoshua Bengio
  3. Guillaume Lample
  4. James Bergstra
  5. Geoffrey E. Hinton
  6. J. Urgen Schmidhuber
  7. Diederik P. Kingma
  8. Alex Krizhevsky
  9. Jacob Devlin
  10. Marc'Aurelio Ranzato

Papers from Mike Kestemont's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Long Short-Term Memory
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Gradient-based learning applied to document recognition
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Going deeper with convolutions
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. ImageNet: A large-scale hierarchical image database

Their papers