Antoine Liutkus

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 6 papers; trusts 56 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

Whom Antoine Liutkus trusts overall

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

  1. Yoshua Bengio
  2. Alex Krizhevsky
  3. Matthew D. Zeiler
  4. Geoffrey E. Hinton
  5. Ilya Sutskever
  6. Po-Sen Huang
  7. Karen Simonyan
  8. Emmanuel Vincent
  9. Diederik P. Kingma
  10. Yann LeCun

Who trusts Antoine Liutkus overall

  1. Naoya Takahashi
  2. Alexandre D'efossez
  3. Romain Hennequin
  4. Daniel Stoller
  5. Laure Prétet
  6. Jen-Yu Liu
  7. David Samuel
  8. Yuki Mitsufuji
  9. Simon Rouard
  10. Fabian-Robert Stöter

Papers from Antoine Liutkus's perspective

Ordered by how strongly the researchers Antoine Liutkus 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. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers