László Lukács

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom László Lukács trusts overall

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

  1. Ilya Sutskever
  2. Oriol Vinyals
  3. Geoffrey E. Hinton
  4. Sepp Hochreiter

Papers from László Lukács's perspective

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

  1. Long Short-Term Memory
  2. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  3. ImageNet classification with deep convolutional neural networks
  4. Dropout: a simple way to prevent neural networks from overfitting
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Et al
  7. Rectified Linear Units Improve Restricted Boltzmann Machines
  8. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
  9. Efficient Estimation of Word Representations in Vector Space
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers