Tamás Mihálydeák

Computational Theory and Mathematics · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tamás Mihálydeák trusts overall

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

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

Papers from Tamás Mihálydeák's perspective

Ordered by how strongly the researchers Tamás Mihálydeák 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  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. Going deeper with convolutions

Their papers