Maria Rigaki

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 147 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Maria Rigaki trusts overall

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

  1. Diederik P. Kingma
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Yann LeCun
  6. Vladimir Naumovich Vapnik
  7. Reza Shokri
  8. Kaiming He
  9. Ilya Sutskever
  10. Nicholas Carlini

Papers from Maria Rigaki's perspective

Ordered by how strongly the researchers Maria Rigaki 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. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers