Thomas Verelst

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 687 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Verelst trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Alex Graves
  6. Ross B. Girshick
  7. Yann LeCun
  8. Diederik P. Kingma
  9. Christian Szegedy
  10. Ilya Sutskever

Who trusts Thomas Verelst overall

  1. Yizeng Han
  2. Jin Chen
  3. Gao Huang
  4. Xijun Wang
  5. Yulin Wang
  6. Shiji Song
  7. Amir Ghodrati
  8. Chenhongyi Yang
  9. Philipp Lindenberger

Papers from Thomas Verelst's perspective

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

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

Their papers