Leonard Adolphs

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 6 papers; trusts 174 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

Whom Leonard Adolphs trusts overall

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

  1. Yurii E. Nesterov
  2. James Martens
  3. L. Eon Bottou
  4. Yoshua Bengio
  5. Diederik P. Kingma
  6. Geoffrey E. Hinton
  7. Yann LeCun
  8. Barak A. Pearlmutter
  9. Alex Krizhevsky
  10. Ilya Sutskever

Who trusts Leonard Adolphs overall

  1. Kurt Shuster
  2. Chi Jin
  3. Jing Xu
  4. Waïss Azizian
  5. Kaiqing Zhang
  6. Mojtaba Komeili
  7. Gauthier Gidel
  8. Hugo Berard
  9. Praneeth Netrapalli
  10. Michael I. Jordan

Papers from Leonard Adolphs's perspective

Ordered by how strongly the researchers Leonard Adolphs 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers